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Transitioning to the FullPull Economy: The case of the UK

Railways

“I am afraid, My Lord, that the London train has just left”

“Well get me another one”

Table of Contents

Transitioning to the FullPull Economy: The case of the UK Railways ........................ 1

Introduction ................................................................................................................ 2

Digital Disruption..................................................................................................... 4

1 Open Standards ............................................................................................... 4

2 Liquification ...................................................................................................... 6

3 Pull economy.................................................................................................... 9

Dynamics of FullPull ............................................................................................. 12

Dominant Design .................................................................................................. 14

Research Design .................................................................................................. 16

Research Question 1 ............................................................................................ 18

Results .................................................................................................................. 19

1 Coercive/regulatory pressure ......................................................................... 19

2 Normative Pressure ....................................................................................... 23

3 Mimetic pressure. ........................................................................................... 24

Research Question 2 ............................................................................................ 26

GSM-R .............................................................................................................. 26

Impact of Dominant Design .................................................................................. 27

Digital Innovation .................................................................................................. 28

Rail Industry Approach ......................................................................................... 30

Customers and Information ............................................................................... 32

Conclusions .......................................................................................................... 33

References ........................................................................................................... 35

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Introduction

The digital revolution is often termed the 3rd Industrial Revolution. It follows the

first Industrial Revolution of the 18th – 19th Century driven by steam, and the second

created by the electrical revolution of the late 19th and early 20th centuries. These

two physical revolutions created huge changes in economies and communities. In

contrast to the changes brought about by new power sources, the digital revolution

(or Information Age) is driven by a transformation in information about both people

and things. For example, information from the sensors on their aero-engines has

enabled Rolls Royce to know much more about their performance and thus change

their design and maintenance; moreover the way in which they charge for usage has

also changed from product leasing to an outcome base, described as “power by the

hour”. Information about people has enabled firms like Tesco to gather huge

amounts of data on individuals’ buying habits, whilst information about networks of

small firms is enabling banks to lend to groups of small businesses in the building

trade rather than just individuals.

We contend there are two distinct processes at work in the digital economy:

digitisation and datafication. Digitisation refers to the process by which analogue

content stored in books, music, photos or other information products is converted

into formats that can be stored on digital media, e.g. MP3 files, CDs, and eBook

formats. This process has been going on since the beginning of the computer

industry in order to speed up the processing of financial information such as payroll

and accounting. The rates of change of the digital technology industries is such that

we now have the processing and storage capacity to store, move, combine and

analyse significant quantities of data in a way we have not been able to previously

(Manyika 2011). This has significant implications for business models and the way

in which value is created and captured.

Datafication (Lycett, 2013) refers to converting aspects of human existence into

data, for example, what I look at while using Google Glasses, or what I tweet about

while in a restaurant, into digital formats. This sort of data provides new insights that

offer huge opportunities for the way organisations conduct their business. Fitbit is a

device that allows end-users to record and monitor their physical activity and collect

contextual information about calories expended and food consumed, as part of a

health and wellness regime: often termed the Quantified Self Movement (Wolf et al

2010). The personal data allows Fitbit to create new business models, based on

selling this information to insurance companies to enable them to better understand

the actual and potential behaviour of their customers and thus better calculate risks.

Datafication, in contrast to digitisation (the conversion of analogue to digital), relies

on sensors and actuators to generate the contextual data about a person or an

object and on data capturing the content and metadata of their digital existence, and

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even how they are feeling. We can also distinguish between passive or automatic

sensors and actuators which cannot choose whether to generate data for example

on location, companions and in some cases activity, and on active or voluntary

sources, showing what the person chooses to contribute, such as tweets, uploaded

photographs and social media status updates.

Figure 1 Digitisation to Datafication

The extent and nature of the disruption to economic and business models caused

by the digital revolution was recognised by Normann (2001). In his widely cited text

(800+ citations), relating to new economic models emerging from the digital

revolution, he considers how dematerialization (the removal of information from a

specific physical artefact) makes it possible in principle for information to exist

everywhere and in real time, [P31].This in turn creates what he describes as an

expanded value space in which offerings are no longer constrained by a particular

geography. [P33]. As Normann points out it is not the dematerialisation that is

important, since this has been around a long time (consider for example of the

semaphore developed in 1792), but the ability to de-materialise information about

almost any asset be it physical (goods or people) or information that is so

challenging and provides huge opportunities for new business models to emerge.

The growth of peer to peer lending and crowdfunding uses the dematerialising

qualities of digital to bypass established financial players and directly link

Ease and speed of

storage, reproduction

and processing of

information

Digitisation

Change in

dominant data

storage formats

Integration of multiple

digital data sources,

both passive and

active

Datafication

Proliferation of

actuators and

sensors

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entrepreneurs to individual funders, which could remain individual (as in peer to peer

lending) or aggregated (as in crowdfunding). Other examples of dematerialisation

may be found in insurance (the rise of facebook groups for risky sports insurance),

retail (automatic replenishment to the home) and farming (data on cows is collected

to increase yields).

Digital Disruption

In their 2013 technology report, Accenture argue that ‘‘every business is [now] a

digital business”, whether the organisation recognises it or not. They suggest

that the digital mindset is no longer the realm solely of the I.T. department within an

organisation, but impacts every area of the business including HR, Property,

Finance, Strategy and Operations; in effect every budget is an I.T. budget1. The

implications of this are being played out within many organisations. For example, in a

recent research interview the Operations Director of Lloyds Bank said that it was

‘inconceivable that anyone in the future could be in his post without an IT

background’. Intriguingly, he did not have that background and was shortly to leave

the company. Digital is not only transforming what can be done, but how it is done

and by whom.

In their 2014 report, Accenture go further and emphasising the scale of the disruption

suggest that the world is at a significant ‘inflection point’ and that the next 3 years is

about determining an organisation’s place in the digital world.

The academic literature (Normann 2001, Vargo and Lusch 2008,Cusumano and

Gawer 2002, Gawer 2011, Narayanan and Chen 2012, Hagel III, Seely Brown, and

Davidson 2010, Ng I, Scharf K, Progrebna G, Maull R 2013 ) supports the view that

key features of this digital disruption are open standards enabling the development

and exploitation of multisided platforms, liquification in which digital and physical

boundaries are increasingly blurred, and the growth of a “pull” economy, in which all

goods and services are provided on an “on demand basis”. We will now consider

each in turn.

1 Open Standards

A technology standard can be considered as “a set of specifications to which all

elements of products, processes, formats, or procedures under its jurisdiction

must conform” (Tassey, 2000, p. 588) or more broadly a technology that “is

accepted for current use through authority, custom or general consent” (p.

417) (Hemenway, 1975)

These standards may be internal or external to the firm, be mandatory or voluntary,

be government or firm/industry driven, and as the definition suggests, be applied to

1 Gartner report http://www.sci-tech-today.com/story.xhtml?story_id=030003CLVSY6

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the characteristics of products and services, the performance of processes, or to the

structure of concepts (eg languages).

Standards enforce compliance with a set of rules in order to derive a private or public

benefit. Among these benefits are the creation of network effects and the reduction

in entry, co-ordination and transaction costs for agents acting in a system. The

much earlier adoption in Europe of an open mobile telephony standard (GSM) than

that achieved in the US created a wider and more established user base more

quickly.and facilitated the introduction of a chip card technology.

Standards come in many forms and arise and develop through many different

administrative processes. The purpose is to obtain agreement or compliance

amongst agents who may have conflicting interests. These processes may be “club”

based, regulator based, or supra national based; for instance the ITU-T which is an

agency of the United Nations governs the development of telecommunications

standards.

Standards encourage interopability (eg containers and pallets) which can lead to

disruptive effects in proprietorial systems and associated rent, but can equally be

used to enable trade restrictions (eg Accounting Standards and qualified auditors).

They also frequently incur development and compliance costs, and can prevent

activity ranging from discriminatory pricing through to illegality.

Competing standard sets can create competing but viable ecosystems (eg Apple and

Android) where standards exist in similar but incompatible architectures, and equally

numerous examples of standard wars (eg VHS and Betamax, Brunel’s broad gauge

and UK standard gauge) where allegedly inferior products created a stronger

ecosystem leading to the superior product’s demise.

Standards can exist in both the analog economy (eg containers) and the digital

economy (eg the mp3 file compression format, or application programming

interfaces: apis) where the development of such standards has been critical to

growth and expansion.

Standards can be viewed from the demand side eg consumer driven standards that

allows integration across multiple products (Axelrod et al 1995, Cusumano et al

1992) or from the supplier perspective where it represents a synthesis of design

rules (Tassey 2000, Tushman and Anderson, 1986; Weiss and Birnbaum, 1989).

Standards exist on a spectrum of openness – from closed and proprietary through

competing ecosystems to full open standards. Open standards are characterised by

being generally available, without restrictions on use or change, and developed by a

mutual community consensual process. In the digital economy open standards can

be seen as being accompanied by open formats and open source software.

The influence of standards, especially open standards, along with open formats and

open source, can be seen in the development of platforms, particularly in the ICT

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sphere. A platform is a part of a production / consumption system made up of the

platform, interfaces, and complementors. The platform “is a set of stable

components [in a system] that supports variety and evolvability in a system by

constraining the linkages among the other components” (Baldwin and Woodward

2009).

The system is characterised by low variety and high reusability in the platform, and

high variety and low reusability in the complementors, with the interfaces, subject to

standards, representing thin connections between the two parts. Baldwin and

Woodard (2009) demonstrate that interoperability is achieved through a set of rules

on design and rules on “decision rights”; broadly “who” can react with and change

“what”. The interface rules act as a fixed point in the architecture. An example of a

platform is the Apple iPhone, with api standards both constraining the interface, but

enabling a vast number of develops to construct applications to run on the “platform”.

The advantages of the open source standards are the creation of large numbers of

small scale developers, creating both a more efficient market, and meeting a much

greater variety of potential demand.

Womack, Jones and Ross (2007) described the shipping container, an empty metal

box often with a wooden floor, which disrupted shipping and handling of goods

sufficiently to make (analog) globalisation possible and easily achievable. We

suggest that open standards will perform a similar role for digital disruption, by

allowing connectivity and speed of information flows, (rather than a better way of

catering for the requirement to move material across time and space). The use of

open standards to allow markets to develop based on a wide variety of demand

being met by a large number of suppliers across stable operational platforms will

stimulate and allow the growth of new business models and enable the constant beta

world suggested by Accenture.

2 Liquification

A major thrust of the digital economy is the recognition that a physical device is not

simply a collection of materials. A commercial aircraft for example, is much more

than a collection of specialised metals and plastics: it is also a carrier of information.

The more that Rolls-Royce are concerned about the utilisation of the aero-engine

the more they are interested in information about its performance.

This blurring of physical and digital is occurring across industry types. Yoo (2012)

describes how the convergence of GPS, digital mobile technology, in-car navigation

and entertainment systems and on-board microprocessors not only enables novel

features for the car but also has had an impact on related industries such as

insurance, safety and car maintenance. Such changes provide a fundamentally

different basis for the design of the vehicle (Henfridsson and Lindgren 2005). As a

result, each modern car now has around 100 million lines of code; in comparison MS

office 2013 has around 44 million. Rolls Royce have long embedded sensors within

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their engines to inform their maintenance and repair, leading to a massive reductions

in maintenance year on year and impacting on their design processes. Other

examples include sensors embedded in running shoes, Samsung’s simband which

can measure a range of health related characteristics, Tesla’s use of multiple

sensors in their electric cars, houses with automated heating, lighting etc.

This ability to separate the information from the physical world requires a special

infrastructure. Rolls-Royce use a collection of sensors and telemetry to collect data

on engine utilisation. Once this infrastructure is in place then information is free to

flow: it has been dematerialised. An immediate effect of dematerialisation is

liquification or the movement of information across the digital infrastructure and its

combination with other liquefied assets to potentially create new insights. Digital

technology makes it possible for almost any asset to be dematerialised and since

this information is quickly liquefied this produces new markets for the information.

Normann (2001) suggests that the analysis of the company should begin from the

interface of the customer and company not from the perspective of production or

product. For Normann, the customer relationship, not the production activity

represents the decisive business potential. This idea has been developed and

refined by developments in the academic marketing literature that have further

emphasized this central and active role of the customer. This is exemplified in Vargo

and Lusch’s (2008) work on service dominant logic (SDL). In SDL customers are

recognized as “active participants in relational exchanges and coproduction” (2004,

p.7); goods are an appliance for the delivery of the service and value is only

determined by the customer according to value-in-use. In their recent work Lusch

(2011) et al. (2010) propose SDL as a framework for the integration of marketing and

supply chain management. They argue that SDL brings not only the suppliers into

the supply chain but also the customer (endogenous) in a process of co-creating

value in a value network perspective. This is similar to Normann and Ramirez’s

(1993) concept of a value constellation where economic actors join together to

create new businesses or radically alter the way that value is created. Normann and

Ramirez stressed that this is not a simple re-allocation of activities amongst the

actors but a new and coordinated set of activities that result in a new kind of output.

Taking this perspective the provider can now be seen as an organiser of value

creation. The customer is not just the receiver of the product or a source of business

but is now a co-producer and codesigner. In Figure 2 Impact of liquification’ below

Normann typifies this by mapping the producer’s view of the customer which

develops over time against technological progress (latterly moving into digitisation)

from a simple receiver of products, through a source of information, to a valued co-

producer with the associated competencies needed to serve this changing view and

role. These competencies start at production, moves to relationship management,

and finally to the organisation of value creation. A simple relationship exists between

the two axes of view of customer and competence over time, leading to 3 phases of

“production” named by Normann as “industrialisation”, “customer base (ie

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relationship) management” and “reconfiguration of value based system”. In the latter

”producer” and “customer” combine to create value together organising their

respective competencies and resources in an “expanded value space”.

Figure 2 Impact of liquification

For Normann (2001), digital technology liberates us from constraints of

1. time, when things can be done

2. place, where things can be done

3. actor, who can do what

4. constellation, with whom it can be done

Taken together these concepts enhance density, ie the best combination of

resources mobilised for a particular situation, for example a particular customer at a

given time and place. This implies ever increasing individualisation. What used to be

a bundle of activities put together within one legal structure and in one geographical

position is now in multiple geographical positions brought together by multiple legal

entities. Ultimately, density means that the customer would have a whole world of

specialist knowledge available when and where they like, creating the “on-demand”

economy. Normann, summarises the process as,

Dematerialize (separate information from physical) - unbundle

(physical/informational) – asset liquidity – rebundle – density

A good example of liquefaction in practice is the RCUK funded “HAT” (RCUK 2014).

The HAT explores a rich picture of the lived life through using sensors and platforms

which offer the opportunity to collect data in far more detail on how individuals

interact with people and objects on a daily basis in their homes. Currently most of the

incumbent resources in the home have not been designed for connectivity or for

integrated use. As technologies become increasingly embedded in objects, and

electro-mechanical interfaces will evolve to connect older devices such that they all

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work together, information will be collected on how things are consumed in context,

rather than simply purchased. Such connectivity will allow business models based

on physical objects, such as the kettle, to be instructed to boil remotely by the home

owner in time for their arrival, or software solutions to provide data to the homeowner

as to the temperature, delivery of post etc.

As a result, new archetypal actors will emerge:

market makers for new infrastructures

large corporations who use dematerialised assets and their infrastructures for

re-bundling different part of the physical world on a global basis

small entrepreneurs. The new logic of value creation creates even more

incentives to scale.

3 Pull economy

We consider that the combination of open standards (eg APIs) and liquification of the

material and enabling the development of the ‘pull economy’ (Bollier 2006). The pull

economy places the consumer at the centre (rather than being producer led) and at

the extreme will draw on resources only as they are used. The roots of the notion of

‘push and pull’ are often associated Just-in-Time and other related manufacturing

techniques.

In manufacturing, the concept of pull is where a downstream work station “pulls” the

item of production towards it when it has available capacity and is a key feature of

the Toyota Production System (TPS). Ohno (1998) asserted that the purpose of the

TPS was to shorten the time between cash and order. The essence of pull is hence

to reduce time and stock consumed in production.

A simple illustration of push vs pull is shown below. In a pure push system material is

“pushed” between work stations often based on a forecast demand and built to stock

In a “pull” system material still moves between work stations but the signal comes

from a production point later in the process. Once an item has been bought by the

customer than a signal is sent “upstream” to make another unit. Kanban systems

regulate the number of items in the intermediate work stations.

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Figure 3: Push and pull compared (Hopp and Spearman 1996)

The requirements of simplifying and achieving flow are well established: frequent

change of product within defined product groups, reasonably certain volumes

allowing load levelling, and sorting product into what Parnaby (1995) referred to as

“runners” and irregular runners (now more often termed “repeaters”) and “strangers”.

He considered that irregular runners could not achieve sufficient volume or load

levelling and should be dealt with in an off line job shop.

One of the well-known features of a pull system, the reduction of work in progress or

stock being worked on in the “line”, can be extended to the economy and therefore to

other factors of production. The first easy carryover is, as Ohno (1994) suggested,

the reduction in the amount of cash working capital “tied up” in stocks of raw

material, wip or finished goods, at any point in the supply chain. The less obvious

carryover is in the other factor of production, i.e. labour. A pull system applied to

labour means that labour would only be used when there is a demand for the

product. Producers would not load balance on the back of planned orders but would

only commit to use labour when it was needed on the basis of demand. This is a

logical and possibly necessary extension of the use of zero hours contracts, where

the risk and monetary cost of spare capacity is removed from the manufacturer to

the workforce, and labour is not compensated for idle time. Consider an example

from the parcel delivery industry. In major cities, the major parcel delivery companies

are facing increasing pressure from companies who offer local delivery using ‘white

vans’, motorbikes or even bicycles. These micro businesses can offer much cheaper

solutions; however the trade-off might be reputation and trust (breakage or loss, )

and service quality (timeliness). Companies such as “SHUTL” (SHUTL.COM) have

addressed this problem by developing a platform where major retailers can offer very

short delivery times (sometimes less than an hour) by employing individual van

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owners, motorcyclists etc all of whom are agents who are on call and can bid for

delivery jobs. For such a system to work, however, there must be an excess or stock

of freelance deliverers so there is always somebody available to make deliveries.

We contend that a pull economy will increase the use of zero hour contracts. This is

analogous to the use in TPS, often hidden, of a large number of very small upstream

suppliers on whom the risk is effectively placed. Taking supply side pull to its

limits/logical conclusion means not making to stock but making to order, or on

demand.

Demand side pull

Pull has traditionally assumed to begin with a customer order and the literature

naturally focuses strongly on the supply side; but we argue that in the world of

datafication the concept can equally be applied to the demand side (consumer) and

that this will be enabled by all facets of digitisation.

The demand side is an area less well explored. The demand side equivalent to TPS

would be shortening the time between need/want and fulfilment. With pull from the

customer being made possible, the customer will not need to hold stocks of e.g. coca

cola. It will no longer be a producer aspiration for the whole world to be within an

arm’s length of a tin of coke, but for the whole system to be capable of delivering the

tin whenever and wherever the need arises. Demand side pull will be enabled by

demand side developments (among which will be datafication, big data, predictive

technologies) complemented by supply side changes (eg platforms, 3D printing).

We contend that this will enable the “fullpull” economy, in which there is pull both on

the supply side and the demand side.We argue that “big data” is not only about

collecting data on certain facets of many people, but also more complete data about

the single individual (sometimes called ‘small data’ Estrin 2014). This has certain

implications. More detailed and predictive demand information will become available

to both the consumer (and his chosen agents) and the producer.

“Strangers”

Digitisation brings with it increased information. This improved information about

each and every customer, and other digital effects (eg 3D printing) reduces scale

effects and facilitates making money out of the hitherto inaccessible or too costly

customers who fall into the “long tail”.

We contend that the long tail is the digital equivalent on the demand side of

Parnaby’s “strangers”, who will now be provided through the same digital channels

as other consumers.:everyone will be a “market of one”.

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But what of unknowns, those goods or services that could easily be provided by the

supplier but aren’t yet being so? If Accenture are correct in their assertion that

supply will be in constant beta, then any unmet demand could quickly be catered for.

Central to the modern concept of the customer is their role as “resource integrator”

(See Vargo and Lusch earlier). They sit at the centre of a complex system of

suppliers and other consumers co-creating value in use and context. We suggest

that this is similar to Parnaby’s notion of the manufacturing “cell”, and thus forms

another element of demand side pull.

Dynamics of FullPull

We have conceptualised the movement to a full pull economy in the following

figures. The axis are push-pull is as described earlier and individual-mass which

represents the market for the provider/producer.

In the individual-pull quadrant we have an industry driven by make-to-order eg

professional services or bespoke furniture. In the top left we have a traditional large

scale manufacturer or service provider who makes to stock as reaps the benefits of

economies of scale.

The development of standards and liquifaction has enabled providers to move into

the area of individual-push where they can individualise offerings in other words sell

more. These personalised adverts enable amazon to be highly specific about

recommendations and to drive sales.

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Figure 4 Digital Economy PUSH

However, selling more isn’t the real focus of a ‘pull economy’ In a world of the

‘market of one’ data is collected from active devices eg my social media updates and

passive devices (eg home sensors). Together these enable personalised data

(sometimes called ‘small data’ Estrin 2014) which will enable organisations to

personalise products or medicines or services to the individual.

Figure 5 Digital Economy PULL

Individual Mass

MTO, Bespoke

Professional services

MTS

Economy of Scale

Pull

Push PersonalisingBig Data I

Sell more stuff …..

Long tail

Probabilistic – deterministic?

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These changes from push-pull are only now being considered by organisations

through their systems design and in our view has the potential to influence all

sectors, industries and communities . The challenge is to consider which industries

will adapt quickly and those which will have deeply held cultural limitations in

adapting their business to the demands of the digital economy.

Dominant Design

In considering how the drivers and the movement from push-pull will lead to a re-

framing of the Digital Economy we have drawn upon Normann’s framework based on

a consideration of levels of aggregation and “time framing”.

Normann develops a simple 2x2 matrix that has on one axis systemic “logic” split

into higher and lower, the movement between two being described as up framing

(towards the higher) and down framing (towards the lower).. Up framing moves

towards higher levels of abstraction; up framing allows us to see more structure and

pattern, down framing to see more detail.

The second, horizontal axis is more complex and involves the “movement” not of

perspective but of time: we see ‘now’ in terms of the conceptual ‘past’ (framed by our

mental models) and the conceptual “future”. Moving into the conceptual future is

about creating a different future by actions now and the concepts that we bring from

the past.

Figure 6 re-framing the Digital Economy (Normann)

The most interesting quadrant is the upper right:upframing in the conceptual future.

However as Normann notes the challenge is “distancing”: the ability to take stock of

what we have, yet distance ourselves from it. This enables us to release decision

making about the future from our previous experiences, instead embracing the

challenge of creating the “new”.

Higher Systemic logic

Lower Systemic logic

Conceptual futureConceptual past

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Being able to create a distance from what we have is inversely related to the concept

of the dominant design (DD). This is those design features that have become an

unchallenged industry standard and which Abernathy [1985] identifies as passing

through three distinct phases:

1. the introduction of a solution which has broad appeal based on performance and basic functionality;

2. a second phase where competitors develop similar designs; 3. this imitative behaviour enforces standardization throughout the industry and

almost complete diffusion of similarity across markets.

Svahn and Henfridsson (2012) point out some of the operational features of this

dominant design: how the entire organisational system is configured with an upfront

design, components are sourced and products built, competition advantage comes

from co-ordination and the use of command and control and hierarchical

organisations. The more an organisation knows its processes and scripts and

controls staff behaviour the more it locks itself and the industry into its dominant

design. The knowledge of how to “deliver” the dominant design is then (Henderson

and Clark 1990) strongly embedded in organisational structures and business

processes in an ongoing re-inforcing loop.

The distancing from a dominant design requires a transformational shift. Tushman

and Anderson (1986) considered these transformational periods across three

industries: cement, airlines and minicomputers. They considered technological shifts

of the dominant design as being either competence destroying or competence

enhancing (Abernathy and Clark 1985). Competence destroying changes require

new skills, abilities and knowledge which fundamentally change the competencies:

for example, diesel locomotives require new skills and knowledge that steam engine

manufacturers did not possess. Similarly, computer numerically controlled machine

tools required major changes in engineering processes and data processing skills.

Competence destroying creates a new completely class of product or substitute for

an existing product or a completely new process: for example the float glass

processing glass manufacturing or mechanical icemaking substituted for natural ice

harvesting.

Competence enhancing discontinuities are an order of magnitude improvement in

price and performance that builds on existing knowledge: they do not render

obsolete existing competences. Examples include the introduction of fan jets or the

screw propeller which dramatically improved the speed of jets and oceangoing

steamships. It is important to recognise that a major difference between the two is

that competence destroying discontinuities disrupt industry structures as the skills

and knowledge that brought product class leaders to pre-eminence are rendered

obsolete.

One of Tushman and Anderson’s (1986) major findings was that discontinuities

occurred only eight times in the 190 years observed across three industries. Yet

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when they did occur these major shifts significantly altered competitive

environments.

A closely related stream of research can be identified in ‘Institutional logic’. Scott

1995; 2005; 2008) identifies three components to Institutional Logic:

1. regulative ie rule-setting,, 2. normative ie the prescriptive and obligatory dimension 3. cultural-cognitive elements which are the shared conceptions.

Each of these offers a different rationale for claiming legitimacy whether by virtue of

being legally sanctioned, morally authorized, or culturally supported (Scott 2008: 51).

Thus, it makes a difference whether an organisation complies out of expedience (to

avoid a punishment), because of a morally obligation to do so, or because it cannot

conceive any other way of acting. But at the same time, each is properly seen as

providing or contributing to an institutionalized social order: all support and sustain

stable behaviour.

Taken together these form three different pressures to conform which have been

characterised as:

1. Coercive pressures. These result from strong linkages to other industry

agencies and institutions and are often in the form of pressures, compulsions,

enticements/inducements and requests. They may also take the form of

governmental measures, guidelines regulations or laws.

2. Normative pressure. These guide decision making and come from the

development of criteria and guidelines which influence judgements and

outcomes. Organizations conform because of behavioural expectations. These

pressures usually result in rules of thumb, standard operating procedures, and

occupational standards (Hoffman, 1999).

3. Mimetic pressure. These are associated with copying or mimicking other

organizations’ systems, policies, processes and structures. In other words,

organizations model themselves after organizations in their external environment

that they see to be similar but also legitimate and successful (DiMaggio and

Powell, 1983).

Research Design

The aim of our research into digital disruption is to examine the key question: will

digital disruption affect all industries or be limited to some? And if so, why, and what

impact will dominant design have in resisting or encouraging digital disruption?

To explore the characteristics and impact of dominant design on a specific industry,

we used the case study research method. Yin (2003) defined a case study as a

method to examine: (a) a contemporary phenomenon in its real-life context,

especially when (b) the boundaries between phenomenon and context are not

clearly evident.

17

It is also recognised (Lewis and Brown 2012) that single case studies can be

particularly useful in the early stages of theory building and also that they are

“appropriate for completely new exploratory investigations” (Meredith 1998). Voss,

Tsikriktsis and Frohlich (2002) also recognise the advantages provided by single

cases in providing greater opportunities “for depth of observation’.

Our rationale for the choice of industry in which to conduct our analysis was based

on the identification of what we considered to be an ‘extreme case’ (Siggelkow

2007). Specifically, we were interested in sectors with long histories of technology

development within well established and relatively stable technology standards,

without apparent evidence of recent disruption and then to consider their approach to

digital disruption.

The UK rail industry is often recognised to be an industry where base technology has changed relatively little in almost 200 years and that there is a huge challenge in

“managing today the Victorian legacy of a railway that was substantially built in the

century before last.

“Network Rail Strategic business plan for England and Wales Jan 2013 p4

Specifically, of the 800 signalling locations over 500 of these are the Victorian signal boxes (Chapman, 2013) and mechanical interlockings are widespread throughout the network and often still regarded as ‘modern’ (despite the first installation being in 1843). In the rail industry press it is often argued that the industry is something of a laggard in the adoption of new innovations the pace of innovation in railways might well be perceived to lag behind other industries just a bit too much. (Rail Engineer, 2013)

“The post-war modernisation of British Railways saw the introduction of ‘panel’

signal boxes covering many route miles on busy main lines… With a nominal life of

25 years, many panel boxes are still in service today 50 years later, although some

of the installed kit has been refurbished or replaced in that time. Watford Junction

(1963) is due to be decommissioned this year whilst Plymouth (1960) is still going

strong.” (Rail Engineer, 2014)

In the academic literature Schilling, (2002) in her widely cited article (273 cites) on

the consideration of the management of technology standards, points to the

importance of network externalities in leading to “technology lockout” and identified

railways as the classic example of an industry with strong externalities.

In short, we consider the rail industry to be an interesting and in many respects, extreme, case, characterised by large scale capital expenditure, a strong culture built on safety, heavily regulated and with well-established networks and infrastructure. All of these are typical features of a ‘dominant design’, an industry in which practices, norms and decision making strongly influence actions and strategy.

Research Questions

18

From the above considerations we generated the following two research questions

1. To what extent does the rail industry have a ‘dominant design’

2. How is the dominant design influencing the rail industry’s approach to digital

disruption?

Research Question 1

In addressing RQ1 we considered the three main pressures of a dominant design

outlined earlier.

1. Coercive/regulatory pressure. These result from strong linkages to other

industry agencies and institutions and are often in the form of pressures,

compulsions, enticements/inducements and requests. In the rail industry

coercive pressures can come from many forms e.g. National Rail, Train

Operating Companies, Department of Transport, Office of Rail Regulation

2. Normative pressure. These guide decision making and come from the

development of criteria and guidelines which influence judgements and outcomes. Within the rail industry these would include formal training regimes for particular job roles.

3. Mimetic pressure. These are associated with copying or mimicking other

organizations’ systems, policies, processes and structures. Within the rail industry this might include adopting practices that are deemed acceptable to regulators which would include a strong tendency to stay within the “industry” for solutions.

Data was collected through three sources:

1. Context interviews with academics, journalists, informed observers and other

industry sources to gain a broader perspective on the industry’s challenges.

2. Analysis of secondary data. A wide range of publicly accessible data is

available through industry and government websites such as NR, ORR, DfT,

Parliament and trade journals.

3. Semi-structured interviews with five members of a leading industry supplier.

(The firm are one of only 2 organisations to achieve an A rating in the Network

Rail suppliers league table2.)

Our approach to data analysis was to review the data collected from our interviews

and subsequent follow-up written correspondence and to characterise the data into

the three headings of regulatory, normative and co-ercive pressure.

2 http://www.cnplus.co.uk/news/sectors/rail/two-firms-top-network-rail-contractor-league-

tables/8653780.article#.U0uls_ldXKE (retrieved 14th April 2014)

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Results

1 Coercive/regulatory pressure

The rail industry has a wide range of stakeholders3 including

Rail infrastructure

o Mainline network

o Underground railways

o Light rail and tramways

o Minor and heritage railways

Legislative framework

This is shaped by both UK and EU legislation.

Government

o Department for Transport

o Office of Rail Regulation (ORR)

o Transport for London

o Transport Scotland

o Welsh Assembly Government

o Department of Regional Development, Northern Ireland

o Passenger transport executives

o European Railway Agency

Safety bodies

o Rail Accident Investigation Branch – responsible for investigating rail

accidents.

o Channel Tunnel Safety Authority – the independent safety authority for the

channel tunnel.

o Rail Safety and Standards Board - builds industry-wide consensus and

facilitates the resolution of difficult cross-industry issues.

o British Transport Police – the national police force for the mainline

railways, the London Underground system, Docklands Light Railway, the

Glasgow Subway, the Midland Metro tram system and Croydon Tramlink.

o Health and Safety Executive - the HSE gives advice to the Government on

health and safety matters.

Industry companies

o Network Rail (NR) – the rail infrastructure owner and operator.

o Train Operating Companies (TOC) – who operate passenger trains.

o Freight Operating Companies (FOC) – who operate freight trains.

3 http://webarchive.nationalarchives.gov.uk/20091113075715/http://www.rail-

reg.gov.uk/server/show/nav.114

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o Rolling Stock Companies (ROSCO) – who own and lease trains to train

operating companies.

o Passenger support – information for passengers about how to make a

comment or complaint about train companies.

o OEM’s - the industry is characterised by a small number of large trans-

national companies, eg Hitachi, Siemens, Bombardier

The principal relationships between these stakeholders have been represented

pictorially in the diagram set out below in Figure 7. The bodies contained within the

hatched area are regulated by the Railways Act 2005. The diagram demonstrates

the extent of interlocking relationships and governance.

Figure 7 Rail Industry Structure

From our interviews and data analysis we identified a number of examples of the

influence and importance of the industry structure on regulatory pressures.

Specific issues include

Industry Structure.

The rail industry has an enormous number of organisations making for a highly

complex eco-system. For example, Wikipedia currently identifies 26 different Train

Operating Companies (TOCs)who in turn lease rolling stock from nine different

Rolling Stock Operating Companies (ROSCOS) and a further 5 spot hire companies.

The importance of the Office Rail Regulator (ORR) is considerable

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“In 2006 responsibility for railway-related health and safety regulation was

transferred to the Office of Rail Regulation creating a single economic and safety

regulator for the railway.” (Network Rail How we are regulated, 2014)

Not only do the ORR have a wide regulation role, but there is also governmental oversight: “The ORR has a very significant role to play in the rail industry including:

Overseeing safety Ensuring free and fair competition Approval of certain licenses and contracts Determining funding and efficiency targets for Network Rail

… The Department for Transport (in England), Transport Scotland and the Welsh Assembly Government set public policy for the rail industry which includes funding of Network Rail, investment in rail enhancements and management of freight grants. “ (Network Rail Regulatory Bodies, 2014)

and this regulator continues to exert considerable regulatory force

“In the next few months, ORR will review our plans in detail. We expect ORR to be

challenging in seeking value for money for taxpayers and railway users.” (Network

Rail How we are regulated, 2014)

When the multiple parties providing services to Network rail are accounted for its

clear that this is a highly complex structure, summarised by one interviewee as

The separation of signalling, rolling stock, civils, track etc. means that system level

innovation is rare and significantly difficult to achieve. [technical director]

Control period

The planning period of duration of 5 years, with a significant lead-in period of 18-24

month lead-in process to agree a settlement, is challenging in an era of rapid

technological change.

In effect, plans are being “finalised” and costed 5-6 years before implementation,

which is probably acceptable for building/civil works, but not technology-enabled

asset management.[Projects director]

The… 5 year cycle with simple ‘punish on failure’ mentality means that long-term

investment commitment is problematic and once Network Rail plans are signed off

there is little incentive to challenge [technical director]

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TOC franchise limit4

The relatively short period of time awarded to a frachisee has contributed to some

issues with returns on investment and ‘short termism’. As KPMG report:

Many of the investments or actions that will improve performance or customer

satisfaction in the UK rail industry do not necessarily have a financial payback

over the life of the franchise, even if it is a relatively long contract such as 15

years (and some investments may not generate a TOC financial return over any

time period). (KPMG, 2010)

Impact of schedule 8 and schedule 4 payments.

These payments are payments form Network rail to the ToCs for planned and

unplanned delays.

The impact of the Schedule 8 and Schedule 4 payment regimes, the regulatory

mechanism to provide rewards/penalties based on performance, create cultural

norms around which Network Rail, TOCs and FOCs plan their businesses and model

revenue sensitivities. The focus on delay minutes, and attribution of costs has a

huge industry overhead (lots of people looking at delay attribution cases) and a one-

dimensional view as to what good looks like (i.e. fewer delay minutes) that does not

marry up with what customers want.[Projects director]

History of technical development.

The long evolution of technical developments and associated regulatory changes

makes the industry a complex place within which to introduce change

Large distributed install base of assets introduced over many years to evolving

standards – ….. makes change harder –not helped by vertical separation historically

into Zones [technical director]

Many of these technical developments have, of course, been associated with

‘safety’.

This is the basis of the railway. The primacy of the Rule Book is vital to safe

operation [industry journalist]

This is obviously a key topic for the industry and was commented on by many of our

respondents and the recent history has been neatly summarised

following the post-privatisation run of major accidents (Southall-Paddington-Hatfield)

there was intense government and media pressure on Railtrack that resulted in the

4 Department for Transport Rail Franchising Policy: Analysis of Historic Data

23

chief executive being forced to resign and following the official inquiries into Southall

and Claphan - where signals were passed at danger, , a cowed railway committed to

impossible targets for installing Automatic Train Protection (ATP)

Currently, there is considerable coercive pressure over level crossing safety and the

new Nework Rail Chief Executive [has] recently issued a blanket apology..

[Industry journalist]

2 Normative Pressure

Normative pressures are defined by Khalifa and Davison (2006) as arising from

cultural expectations in which norms and standards of the operating environment are

formed and which in turn guide decision-making. These pressures result in the

development of rules of thumb, standard process, operating procedures and

organisational standards. (Hoffman, 1999i).

In a review entitled ‘why is innovation so difficult in railways’ the authors highlight that the challenge of implementing innovations lies not so much with the technology itself but the size of the physical network and the number of people and organisations that need to be aligned in order for innovations to work.

They highlight 12 ‘subtle reasons’ for the failure of innovative ideas including: new

idea does not fit with existing aging infrastructure; new idea does not fit the culture;

new idea does not fit with regulations and procedures and that the originators of the

idea are not trustworthy according to the railway experts. (The Rail Engineer, 2013)

An example of how current structures limit ways of thinking can be seen in timetabling. Transport for London (TfL,2014) define a frequently used bus service on which “has five or more buses an hour. It's a route where passengers tend not to look at the timetable before arriving at the stop.” This affects the service quality measurement: “For this reason we are more interested in how reliable and evenly spaced the service is. Scheduled arrival times are less important. We aim to ensure buses run at evenly spaced intervals and do not 'bunch'.” In contrast, Network Rail uses a single service quality measure (“The Public Performance Measure (PPM) shows the percentage of trains which arrive at their terminating station on time.” ) which prevents the consideration of frequency based timetabling, even though there are many routes where five or more trains run, especially in the London area. (Network Rail Performance, 2014)

Some of our respondents have identified the unquestioning nature of these norms

and standard operating procedures.

Standards that are solutions specific and/or are very light on ‘why’. This encourages

a ‘comply’ in preference to ‘challenge’ approach [tech director]

Silent interface standards – instances where there are implied/practical constraints

that are unwritten but embodied in product ‘pairings’ – e.g. leading to a focus on

extensive EMI testing of new trains on miles of instruction rather than being able to

rely evidence of compliance. [technical director]

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Explanations for how these standards have emerged so strongly are deeply

embedded in the industries history eg

Poor, incomplete and inaccurate records of the asset base – makes change

undesirable and perceived as ‘dangerous’.[tech director]

These standards are not necessarily formal they may be implicit and encouraged by

the industries tendency to promote from within

Its easy to see how many people in positions of influence (Senior Management) and

blocking (Middle Management) have come through the ranks/railway

supply.[solutions development director ]

The newly formed Rail Executive in the DfT…places experience in rail commercial

environments above everything else. [solutions development director]

Perhaps most importantly, accountability for performance may also be an issue

No performance culture – neither success nor failure brings conspicuous

consequences (tech director]

The consequences of these standards can be seen in the approach to innovation

significant attempts to introduce process and product change (e.g. Signalling

partnerships, Modular signalling etc) are tied to applications projects so that under

delivery pressure the true novelty tends to get scoped out by risk-averse project

managers. [tech director]

Traditionally, it is extremely hard for a supply to attempt to innovate outside of that

which NR have said they will buy. We’re seeing this increasingly coming through

now with the Railway Technical Strategy, So long as you fall within the RTS, you’re

allowed to innovate, but the RTS is just a shopping list for technical improvements. If

you are an established multi-national player, you are in a position to lead, but then

this goes against the increasingly perceived wisdom in technology circles that

innovation and change comes from the SME’s not the giants. [ solutions

development director]

3 Mimetic pressure.

These pressures come from wanting to look like other organisation, in their

processes and functions or structures. These may be inside an industry structure or

outside.

The focus for these particular mimetic pressures appears to come from within the

industry,

Track

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External quantified benchmarking data have been obtained from a number of

European rail comparator organisations, and the cost differentiating factors

analysed…

Signalling

Qualitative and quantitative external benchmark data have been obtained from

European comparator organisations through a number of studies. …

Telecoms

Quantified benchmarking data have been obtained from European rail comparator

through Network Rail’s participation in the formal RTC benchmarking group …”

(Arup, 2013)

It is not only Network Rail that benchmarks itself against the rail industry. The report

“Realising the Potential of GB Rail” (DfT/ORR, 2011) commissioned by DfT and

ORR also compared within the industry:

“International benchmarking has involved selective comparison of the GB rail

industry with similar railways in France, the Netherlands, Germany, Sweden,

Denmark, the USA, Hong Kong and Australia. “

The article concludes by arguing that the industry consciously lags behind in its application of new technology and unless it addresses some fundamental issues will be condemned to the museum.

Not only does the regulator use within-industry comparators for bottom-up, technological benchmarking, but also for top-down, econometric benchmarking:

“Our PR13 econometric analysis used a subset of the Lasting Infrastructure Cost

Benchmarking (LICB) dataset developed and maintained by the International Union

of Railways (UIC) for 14 European rail infrastructure managers, including Network

Rail, covering the period 1996 to 2008. “ (ORR, 2013)

Industry interviews also suggested a tendency to look inside the sector,

There…. seems to be a “norming” effect [of industry bodies], presumably because

you have to get many bodies to be broadly aligned (or at least not offend any of

them), that the radical or novel is often eliminated.[development director]

Much of this norming may be driven by a mindset that begins with the idea that

railways are different….

“The railways are different” – actually in many ways they are – almost certainly a lot

more than they should be. Rail specific solutions make ‘different’ a self-fulfilling

prophecy. Engineers have to invest to enter the market, those with valuable domain-

specific knowledge are reluctant to leave.[Technical director]

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This mindset also has implications for innovation

Traditionally, it is extremely hard for a supply to attempt to innovate outside of that

which NR have said they will buy. We’re seeing this increasingly coming through

now with the Railway Technical Strategy, … So long as you fall within the RTS,

you’re allowed to innovate, but the RTS is just a shopping list for technical

improvements. If you are an established multi-national player, you are in a position

to lead, but then this goes against the increasingly perceived wisdom in technology

circles that innovation and change comes from the SME’s not the giants. [Solutions

Development Director]

Research Question 2

From our interviews we also found evidence of a number of examples of how a

dominant design has restricted the uptake of new technologies. For example, one

interviewee pointed to the reluctance of the train operating companies to adapt their

rolling stock to meet the needs of disabled people even though from January 1st

2020 government legislation will mandate this change. This reluctance applies

across the sector and applies to ToCs and Rolling Stock Operating Companies

(ROSCOs). Similarly, the industry was slow to adopt the benefits of revenue pricing

and yield management preferring to wait for the airlines industry and theatres before

adoption.

An excellent illustration of the limitations of dominant design is provided in the case

GSM-R.

GSM-R

An excellent example of the rail industries approach is illustrated in the example of

Global System for Mobile Communications – Railway (GSM-R). This is the

international wireless communication standard and part of the European Rail Traffic

Management system (ERTMS). It is used to enable communications between the

train and the control centre and to provide both a data link and direct voice calls

between the control centre and the train. As its name suggests, GSM-R is based on

GSM technology and is the result of over 10 years of collaboration to various

European rail companies. We used GSM in section xxx above as an example of

how the degree to which standards are open can influence development of an

innovative sector.

During its development phase became clear that the standard GSM technology of

the time could not meet all the requirements of the rail industry Sniady and Soler

(2012) and the industry set out to develop its own solution. Sniady and Soler (2012)

summarise the shortcomings as including

1. Outdated technology: Mobile telecommunications have evolved substantially

since the development of GSM-R (a 2G standard) including GPRS, edge,

27

UMTS, HSPA and now LTE. GSM-R was designed to take account of a

number of hardware constraints that are no longer valid and was designed

primarily for voice communication whereas today data communication is

becoming at least, if not more, important.

2. Interference issues: GSM-R operates on a dedicated frequency band and it is

becoming apparent that there is interference caused by public operators. This

is unsurprising since both rail and telecoms industries want to provide service

to customers on the train.

3. Capacity issues: GSM-R has limited radio capacity and is based on a circuit

switched mode which is not sufficient for ECTS level 2 which requires

continuous data connection.

4. Limited capabilities: The technology is not flexible enough in terms of

throughput and delay to provide advanced services for example Internet

access for passengers.

5. Dedicated technology: GSM -R is based on a commercial technology adapted

for the railway. It is therefore a dedicated technology used by relatively small

industry and does not have access to the economies of scale that could have

been gained from using more widely available technology shared with

commercial mobile operators or emergency service providers. Secondly, as it

is a dedicated solution, specific handsets had to be developed that according

to our interview data costs around £1500 for each involving many

stakeholders: train operators, unions, national authorities, infrastructure, train

operating companies which have in effect led to the development of a very

outdated technology.

This example illustrates some of the important features of a dominant design. For

example, industry regulation and guidance across multiple countries means it is

difficult to innovate and requires multi-partner agreement. Normative pressures ‘the

railway is different’ guides decision making and leads to a solution that is unable to

reap scale benefits. Finally, accepting already widely established technological

solutions such as GPRS (arguably when it was already outdated) is a classic

example of an industry which is copying so called safe practice from elsewhere.

In the UK GSM-R is fully deployed across the south of the country and the national

roll out is expected to be completed in 2014 and is, as the network rail web site

states, certainly based on ‘trusted GSM mobile technology’5. However, unfortunately

it is widely recognised that GSM is already obsolete at deployment ii and faces the

possibility that it might be switched off within 5 years (Sniady and Soler 2012)

Impact of Dominant Design

There is a substantial body of evidence that within the rail industry that Dominant

Design is strong. Regulatory, normative and mimetic pressures are evidenced from

5 http://www.networkrail.co.uk/aspx/6386.aspx retrieved a4th april

28

press reports, interviews with suppliers and industry members and documentary

information. However, as pointed out by one of our interviewees, the rule book is the

cornerstone to the safety of the industry. It is important to have a strong culture of

compliance in an industry where oversights in safety cost many lives.

This raises the important issue of whether in an era of rapid technological change at

what level of an organisational architecture that maintaining a dominant design is

appropriate and at what level it should be challenged.

In considering the impact of dominant design in the rail industry, it is important to

distinguish between the layers in the technology architecture. To do this we have

used the framework proposed by Brown et al (2014) in their paper on revolutionising

public service delivery (Figure 8). The infrastructure layer is the physical layer that

enables the development of a platform. These platforms should be driven by

capabilities and re-use of technology and may lead to modifications in business

processes as typical organisational structures are inappropriate for platform

development and use. Finally, new communities and clients emerge as the data on

the platform becomes available.

Figure 8 Adapted from Brown et al

Digital Innovation

Innovation in the digital industry is associated with networks or ecosystems which in

turn leads to the emergence of dynamic and nonlinear patterns of innovation (Yoo

Lytinen (2008) reported in Svahn and Henfridsson 2012). Yoo et al argue that digital

innovation is characterised by convergence and generativity. These are based on

the concept of technological affordance “action potential, that is, to what an individual

or organization with a particular purpose can do with a technology or information

system” Majchrzak and Markus (2012)

Convergence brings previously separate user experiences together. For example

convergence has enabled the bringing together of multiple audiences which

previously required separate products for example smart phones can now take

photographs and make voice calls and act as alarm clocks and torches.

29

Generativity is a technology’s overall capacity to produce unprompted change. For

example the development of the smartphone supports generativity through the

establishment of a platform which enables innovations by third parties to be

integrated into the platform after the fact.

Yoo (2013) argues that many of the recombinations of use of Google maps may not

be what Google originally intended or even thought possible when it was first

introduced, for example its use as an emergency coordination and communication

capability during hurricane Katrina. Nor did they anticipate that Nikon engineers

would integrate them with photographs from digital cameras. As Yoo reports on the

development of the Apple IOS it was only when independent developers from the

jailbreaking community introduced unofficial applications created by third-party

developers that Apple embraced generativity and the resulting Apple App Store. In

contrast Google has perhaps allowed too much uncontrolled change in the open

android platform and are said to subsequently introduce metric measures to better

control the core of the operating system, and in May 2014 they prevented the use of

unapproved extensions to the Chrome browser, saying that these could be used as

open doors to the introduction of malware (BBC, 2014). However, the key feature of

generativity is the enabling of open innovation.

In digital innovation innovation is distributed across many parties and agility, the

ability to detect and seize opportunities is an imperative for success in a digital

innovation regime (Brown and Eisenhardt (1997), Christensen (1997). For firms in

such a network they need to recognise that they are part of a horizontally segmented

industry and simply nodes in a value chain network.

In short, digital innovation has many different features to that of traditional product

and infrastructural innovation. Svahn and Henfridsson (2012) summarise these as

falling within 3 key “logic” groups grouped as “organising logic”, “market dynamics”

and “architectural design”. These are set out in Figure 9 below.

30

Figure 9: Logics in digital innovation

Some key features of this analysis of the key differences between IT (new) and

product (traditional) based innovation are the necessity for non-linear processes and

network approaches rather than firm centricity (organisational logic); competition

based on “attention” rather than approach and shared platforms rather than

“dominant design” (market dynamics); and functional not physical structures,

generative rather than modular designs and complexity of design not artefact

(architectural design logic).

Rail Industry Approach

The organisational architecture set out in Figure 7 clearly indicates that the rail

industry is a complex system.

The translation of the organisational architecture into a physical reality reinforces this

view with a large number of connected assets with strong relationships between

them. The activity of routing a train to fulfil the primary task of moving passengers

between fixed stations touches many agents. A primary focus has been safety and

the issue of reliability remains a key challenge. The RTS (Network Rail Technical

Strategy, 2012) accepts this and notes that an approach to reliability similar to that

used on safety would lead to a “step change” in performance.

The Rail Technical Strategy (2013) prepared by major stakeholders in the industry,

represents an attempt to set out and develop a coherent framework over a planning

31

horizon of 30 years, but also to form the basis of more detailed expenditure plans

over the next two control periods, CP5 and CP6. The document is based on a

number of relational “themes” namely Command, Control and Co-ordination, Energy,

Infrastructure, Rolling Stock, Information, and Customer Experience. These are

underpinned by 3 “common foundations” of a Whole System Approach, Innovation,

and lastly People. Enabling the forwards plans are “common design concepts”

which are Whole System Reliability, Resilience, Security, Automation, Simplicity,

Flexibility, and Sustainability. Key targets are described under the headings of “4

‘C’s”, which represent Capacity, Carbon, Costs, Customer satisfaction. To deliver

these ambitious targets a set of key projects is proposed addressing these singly or

together, graded along the axes of benefits and investment in a 4 degree scale from

low to very high.

We have identified a number of these projects which address the impact of digital

disruption most closely. These are a set of projects around big data and information

flows, and others on operational modelling and optimised traffic management.

Although these are having very high benefits, these are seen as occurring in CP6, ie

5 to 10 years away. We consider that this demonstrates a view that these impacts

will be not available to be recognised till then.

As part of the document set an academic response (ARRTS) from sector experts

was also published (RRUKA, 2012 ). Whilst broadly supportive of the RTS, some

significant concerns were expressed. These centre on the difficulty of

overcentralised control. For instance it was noted that the tools were lacking for a

whole systems approach, with optimal control of the whole network made difficult by

the lack of an agreed objective function (eg reliability or cost) and the absence of

appropriate modelling techniques and associated mathematical knowledge. The

modelling issue is confounded by the lack of freely available open data, with an

industry mindset driven by security.

A further area of concern was the apparent failure to learn from other industries;

innovation is seen too often as coming from within the industry. “The most

significant opportunities to enhance current knowledge transfer relate to transfer

from other sectors” ( p11)., with the examples given of auto and aviation going to

autonomous vehicles / platooning. This reluctance to learn lessons from elsewhere

has led to railways taking a path to dumb trains and centralisation.

This view that the rail industry is unaware of the potential impact of Digital disruption,

and its immediacy is reinforced by an analysis in the ARRTS showing that when the

impact of the investment in the 7 common design concepts is mapped against the 6

technical themes, whole system reliability is only concerned to have a medium

impact on both command, control and co-ordination and the customer experience.

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Customers and Information

There is surprising little in the RTS or the ARRTS dealing with the impact of digital

disruption on the behaviour of customers, echoing a general consideration of those

we interviewed that the rail industry does not understand its customers.

The role of information is seen as being separated from control, command and co-

ordination, with “Information” separated from “command, control and co-ordination”

and action to improve customer satisfaction too often seen as better delay

information and contactless ticketing rather than timetable flexibility and recovery.

Customers are not seen as part of the value chain, but as elements to which a

timetable and information is pushed. Alternatives to this model are already in

evidence. For instance, blablacar, a French app based car/journey sharing scheme

is now considered by SNCF (the French railway company) as a major source of

completion. App based solutions to transport which the customer pulls towards them

can also be seen in Uber, a crowd sourced “taxi” solution.

Taken together these pressures can lead to a strong culture that does not change

quickly. They may even provide insights into the way developing technologies have

been previously implemented (GSM-R)). However, this may not be limited to the

past. For example, In a recent comment piece in the Guardian Matthews (Matthews,

2014), CEO of a leading industry supplier, sets out 10 ways in which railways in the

UK can be improved. These include: a stronger focus on the passenger that is

moving from simply operating railway based on push principles to focus on service;

recognising that the speed of change is extraordinary and increasing and that

competition may emerge from other sectors; getting things done quicker; learning

from other industries; valuing the role if IT and fundamentally changing the culture.

More fundamentally, she draws this together in a discussion of a specific case: that

of the procurement of a traffic management system. Ford (2014) in his review of the

TM system develops a hypothetical example where a wheelchair passenger is going

to take 10 minutes to board a train and considers whether it is cheaper to delay the

train by 10 minutes or use a taxi. This can only be done using a traffic management

system that can show the consequences of the disruption from a 10 minute delay. In

Ford’s example late running will cause a hundred minute delay plus another 115

minutes due to the knock-on effects. As a consequence, the cost of the delay is now

known and can be compared against a taxi. In summary, ‘TMS allows the signaller to

quantify the chaos of a range of decisions’. However, it is clear that there remains a

significant confusion around what a Traffic Management System is ‘in fact I’m not

sure that Network rail can articulate what a TMS is’ (Ford) and the argument from the

former CEO of NR that TMS is a ‘massive need’ but that the main problem is ‘getting

the industry to accept that it is something they can trust’.

Perhaps most importantly, Matthews argues that the benefits of TM may be being

delayed due to procurement practices based on the use of proprietary technology

from the 1990’s that would be considered obsolete in any other industry’ and these

33

delays are worth £250Bn a year and over £1Bn in control periods 5 and 6 (up to

2015).

Conclusions

We contend that digital will be able to disrupt the rail industry in a number of ways.

from both supply and demand side, and its effects on customers may exist in a world

of different pull based solutions. The current strategy underestimates the (potential)

impact of digital and how this will enable all travel customers to pull solutions.

In respect of the Digital Economy: It’s here now (not 2025 as in the RTS) and will

drive customer expectation. By 2020 an entire generation will have grown up in a

primarily digital world (Strategy& 2014) These customers will have a perspective

that the power lies with them as resource integrators within a wider network, and a

range of suppliers will have access to more usable data and intelligence, enabling

them to provide and sell more solutions differently. Value will be created in context.

Digital business is different in being non incremental and being driven by innovation,

not technology, product, artefact or procedure.

The DE impact will be extensive; a paradigm and mindset shift are both required.

Lessons from successful technology platforms confirm that they are built on the

principles of open standards which encourage innovation and grow the market.

Systems should be allowed to evolve and designed for participation with learning

from users, especially from unexpected and unplanned sources, and barriers to

experimentation should be lowered. This is represented in the government agenda

on technology purchase and open data. The generativity provided by digital

disruption creates new businesses, new revenue streams, and open innovation

leads to more ideas, better models, better networks.

Railways are receiving significant investment funds over the next two control periods

but may experience a very different future to that contemplated. Some parts of the

industry appear insensitive to passenger numbers and customer requirements.

Recovery (disruption management and recovery) is too complex to rely on people.

and even more difficult to simulate at train level, optimising passengers is even more

difficult, especially when there is no model and no data. The dominant Mindset is

that of safety and control, with a deep seated concern for accidents, level crossing

incidents and suicides.

The rail industry is not good at technology or the process (of introduction), and still

using waterfall plans in a world described by Accenture as being in constant beta.

The effect of a dominant design is exacerbated by a 30 year mindset based on a

curious amalgam of infrastructure/station life, rolling stock life, and other shorter term

assets. There is a substantial body of evidence that the passenger is on the

receiving end of a push mentality.

34

The digital economy will affect power relationships between all the stakeholders in

the railway directly and indirectly. Directly it will affect who does what and who gets

what. This changes as the Importance of ownership and use of data is realised, and

barriers to entry to the transport business are removed. Indirectly it will bring

different competitors, players and solutions into the industry, impacting on existing

providers, especially those with large fixed costs.

The above discussion clearly is describing a future at the limit. However we can

already see the early signs and enablers of such a digital future; as mentioned above

zero hour contracts and 3D printing, and an increasing ability to create value from

the long tail through the use of big data and accompanying algorithms. We contend

that the argument is not how far but how fast.

35

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