Analysis of Cloud Business Models for the Industrial B2B Market

Analysis of Cloud Business Models for the Industrial B2B Market

Martin W. Krueger∗and Marcel DixABB Corporate Research

Ladenburg, Germany{martin.krueger, marcel.dix}@de.abb.com

Abstract

Cloud technology is by today common in consumer targeted IT markets. In industrial B2B marketshowever, cloud technology may provide added value for the customers, but these markets behavemore traditional and conservative compared to B2C markets and are therefore slower in adaptingthe new technology. This highlights the need for the development of appropriate business modelsaccompanying the introduction of cloud technology to industrial B2B markets. This industrial studyintroduces a new framework for the analysis of cloud business models and examines three B2Bcloud business models from a broad range of industries. It was found first that cloud technology maybe very suitable for B2B businesses, as it poses the opportunity to address multiple roles within acustomer organization at once but with different offerings. Secondly, the examined cloud businessmodels did not replace existing offerings in the respective market, but introduced new added valuefor the customer. Third, the majority of the B2B cloud offerings could also be solved with a service-client architecture, but that a ”cloud” label can support marketing related efforts. This study buildsthe basis for deriving common patterns from B2B cloud business models, which may in the futureenable the efficient development of B2B specific business models for industrial cloud offerings.

Keywords: cloud computing, business model innovation, business model analysis, B2B, industrialcase study

1 Introduction

Cloud technologies are becoming increasingly popular. Most commonly-known cloud-based businessmodels address consumer markets (B2C), e.g. Google Mail, Linkedln, Spotify. B2B business modelsmaking use of cloud technologies to create value to customers usually comprise only the provision andadministration of the technology as such (IaaS, Paas), e.g. Amazon Web Services, Microsoft Azure,Google App Engine. Therefore, there is a need for understanding how B2B businesses, such as theindustrial automation business, can make use of cloud services in order to create an added value to thecustomer, and how such business models can look like respectively. In this study a methodology toderive business models from existing cloud offerings is introduced and subsequently used to analyzecloud business cases from three different B2B markets to foster the understanding of B2B cloud businessmodels and their applicability to other industry markets. Parts of this study have previously been acceptedat the WiWiTa 2014 conference [16]

2 Research Approach

In this industrial study we have analyzed three cloud-based B2B business models on how potential valueis created. The cases were selected from related industries nearby the industrial automation sector, so that

IT CoNvergence PRActice (INPRA), volume: 2, number: 2, pp. 12-20∗Corresponding author: ABB AG, Forschungszentrum, Wallstadter Str. 59, 68526 Ladenburg, Germany, Tel: +49-(0)6203-

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Industrial B2B Cloud Business Models Krueger and Dix

Specific On-Demand Broad Network Resource Rapid Measuredoffering Self-Service Access Pooling Elasticity Service

Medical Imaging [10] 0 2 2 1 1Building management [12, 15] 2 1 2 1 2Internet of Things [11] 1 2 1 2 2

Table 1: Overview of the examined application cases, as well as the test of applicability of the NISTcloud criteria: 0 = not necessary, 1 = supportive, 2 = essential.

a broad view on feasible cloud-based industrial B2B business models can be drawn. These are: medicalimaging diagnostics [10], Internet of Things [11], and building management [12]. For the business modelanalysis we have first gathered information from press releases, product web pages, and trade publica-tions. Next, we structured the gathered information utilizing the Business Model Canvas methodology[21] and checked the business models against the NIST criteria for cloud computing [18] as shown inTable 2. The results were then discussed in the project team, with the long-term goal to identify com-mon patterns in existing business models. The incentive for this is that such cloud-specific ”BusinessModel Patterns” for the industrial B2B-sector could significantly increase the efficiency of developingnew business models in future. Figure 1 illustrates our approach.

Review of existing data

•  Websites •  Press releases •  News articles •  Scientific articles

Stuctured analysis of business model data

Discussion of results in project team

Business model canvas

Refinement of analysis

Identification of value propositio mechanisms

Transfer of business patterns to other

industry segments

Patterns in business models

Test of applicability of NIST cloud criteria

Figure 1: Overview of the utilized research approach. The step of transferring identified patterns inbusiness models is an outlook towards future research studies. Figure based on Krueger, Dix (2014).

3 Special Characteristics of B2B Markets in the Industrial Context

Requirements of business models for the industrial sector (B2B) differ significantly to the consumer sec-tor (B2C). For example, in B2C, a service downtime of 5% is often acceptable or can be made up for withan adequate price discount. In an industrial production, on the other hand, every minute of downtimecan cause millions of Euros loss, so that the loss can be much higher than any discount granted [14].The issue of security also plays a much more important role in the industrial sector than in the consumermarket [14, 19], even despite current security discussion in the consumer IT sector. Furthermore, newtechnologies are adopted faster in the B2C market, e.g. due to an improved usability or simply because

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of their newness [20]. In B2B markets, on the other hand, cost is the decisive factor [20]. The industrialproduction market is much more conservative with regard to making frequent changes to a plant, whilestability of the plant and its production processes is a higher maxim. Today, the adaption of cloud tech-nologies in B2B markets is additionally hampered by a lack of suited service level agreements (SLAs)[14], however, first research in this area is ongoing [1, 2]. The introduction of cloud technologies there-fore also implies the introduction of new service-specific business models in the industry [9] in terms ofa business model innovation, which is discussed in literature under the term of ”Servitization” [8].

4 Value Propositions of Analyzed Cloud-based Business Models

4.1 Medical Imaging Diagnostics

The first B2B cloud-based business example is from the medical imaging diagnostics sector [10]. Thespecific offer aims at supporting IT processes between hospital departments and/or private practices(Fig. 2). Here, the cloud technology is used to exchange medical imaging data in a fast, and easy-to-usemanner, as well as to provide an efficient way to obtain an expert opinion on the images, e.g. with thehelp of annotations. The value proposition to customers is, that he can save a lot of time and therebycost when images can be exchanged via the cloud, as opposed to the traditional handling of physicalpatient’s files. Figure 3 shows the business model canvas for the medical imaging example, as it wascreated during the analysis of the case.

Hospital department / private practice

1


2


3


4

Clinical image

acquisition

Interpretation of image data

Treatment

1st Diagnosis & transfer to specialist

com

mun

icat

ion

Trea

tmen

t wor

kflo

w

Figure 2: Illustration of the investigated example in the field of medical imaging. In the course of theimaging-based diagnosis, various hospital departments and / or private practices need to communicateand share imaging data. This is traditionally done using DVDs and printed letters. This way of commu-nication poses the risk of obscuring or losing data. Figure based on [16].

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Key Partners

Key Activities

Key Resources

Cost Structure

Value Propositions

Revenue Streams

Customer Relationship

Channels

Customer Segments

Hospital departments

Private practices

Customer lock-in: high hardware switching costs

Long-term customer commitment (long product life-cycle)

Online sales?

Secure internet for service delivery

Word of mouth (doctors)

Medical congresses / conferences

Scientific journals

Personal visit (sales)

Regular customer visits

Increased efficiency & reduced diagnosis costs through easy cloud-based patient

image sharing (between hospital

departments and/or practices)

Lock-in through industry standard

established

Sales of cloud solution

IT hosters Cloud IT

infrastructure operation

Sales force

Brand Cloud IT infrastructure

Cloud service personelle

Cloud technology developers

Sales costs

Interface developers

R&D costs Cloud IT costs

Increased sales of medical imaging systems Cloud rental fee (?)

Figure 3: Business model canvas for the medical imaging example.

4.2 Building Management

The second examined cloud business example is from the building management sector [15]. The cloudoffering targets building operators of distributed office or industrial buildings. The value proposition tothese customers is being able to save personnel, as the cloud enables the customer to manage all buildingscentrally from a single location (Fig. 4). One highlighted feature of the cloud-based solution is, forexample, the visualization of building KPIs. Furthermore, optional optimization services are offered,including services from 3rd parties, which can leverage the building data gathered. The customer canbook such services on-demand self-served and can adjust the services on his needs. Figure 5 depicts thebusiness model canvas for the building management case.

4.3 Internet of Things (IoT)

The third example of a B2B cloud-based offering targets the Internet of Things (IoT) [11]. The specificoffer is the provision of gateways that enable customers to integrate arbitrary devices into the cloud andtransfer device data to the cloud (Fig. 4). Here, the value proposition to the customer is that he can easilyintegrate his devices into the cloud without having to worry about gateway development, and therebysaves cost and stays flexible (Fig. 5).

5 Discussion

Creating an added value through cloud technologies seems to be a challenge, especially in traditionalindustry sectors, such as the automation technology industry and industrial engineering that are charac-terized by special requirements e.g. on availability, reaction times, and security. Many B2B applicationstherefore do not fully leverage the technical advantages of the cloud. However, cloud technologies suchas ”Hadoop” and ”MapReduce” can provide an advantage wherever large amounts of data (so-called”big data”) has to be processed and analyzed – and it is precisely in the aforementioned very IT-intensive

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Customer

Building 1 management

Services (e.g. analyses)

e.g. 3rd party

Cloud infrastructure

Central management of

all buildings

Building 2 management

Building N management

Figure 4: Illustration of the example from the building management industry. One customer owningmultiple buildings currently manages all buildings individually using separate building management sys-tems. The cloud enables a central management of all buildings. It may also provide access to 3rd partiesfor providing advanced services for the customer. Figure derived from [12].

Key Partners

Key Activities

Key Resources

Cost Structure

Value Propositions

Revenue Streams


Channels

Customer Segments

Key Resources

Cost Structure

Revenue Streams

Channels

Building operator companies

Consolidated management of all distributed facilities

Private building automation cloud

Back office service staff with cloud

access Existing sales channels to additionally

offer cloud services

Requires close relationship (trust)

to allow service provider access

Back office service staff costs

Cloud solution & cloud service

Cloud IT provider

3rd Party service providers

Provision of remote services

Existing building automation system used by customer

Access to customer data

Better/optimized energy efficiency

Increased system availability

Easy (un-)booking of add-on services via existing cloud

infrastructure

Similar to “BASE” mobile contracts

Easy & efficient on-demand expert

service

On-demand self-service once cloud

technology is established

! Operation view

Private equity companies

Portfolio management

! financial view

Service offerings based on access to cloud

DCS system (transaction-based)

Cloud infrastructure costs

Figure 5: Business model canvas for the building management example.

automation industry where such large amounts of data accumulates. The strong argument for the cloudis not that big data analysis will be able to run faster, be easier or more cost effective [13], but that ana-lyzing truly big data is often possible only with the help of large distributed (i.e. cloud-based) computerresources, whereas the big data can easily drive more monolithic analytics systems to their limits, letthem become instant (e.g. due to insufficient memory). If an industrial customer wants to gain valuable

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Gateway Cloud

PaaS provider End-customer Service providers

Devices

Applications &

services

Figure 6: Illustration of the IoT example. The cloud as well as the device gateway are provided to theend-customer and 3rd parties. The end-customer does not need to connect every device individually withhis system and can benefit from services from service providers. Figure derived from [11].

Key Partners

Key Activities

Key Resources

Cost Structure

Value Propositions

Revenue Streams


Channels

Customer Segments

Connect any device with open API

Drive productivity up and cost down

Promote business intelligence through data visualization

Manage devices en masse for increased

efficiency

Cloud connector

Complete toolkit for IoT solution

Annual fee per device

Device network operators

Device network application providers

Provide cloud connector

Provide API

Provide device cloud

Device Cloud takes care of isecurity policies

No scaling problems

Comfortable, central device management

30 day free trial

global GSM and CDMA carriers

Free 3rd party developer accounts

Cloud IT R&D Tech support

Support for 3rd party developers

Web shop

IT framework

Free development framework + open

source code

Free software code

Sales of connection hardware

Professional design services

Figure 7: Business model canvas for the IoT example.

insight into his plant data that he gathered over many years, he may need the cloud. Currently thereare still open legal question how to handle customer data in a non-private cloud [19], which need to beresolved by the legal instances on a global level in the future. From the technical perspective, the addedvalue in some application cases can also be delivered using server - webclient solutions. This became e.g.apparent when testing the B2B cloud computing examples against the NIST criteria for cloud computing.This analysis revealed that the cloud computing offerings do not fulfill all NIST cloud criteria to the fullextent (Table 2). However, ”cloud” can in these cases be used for marketing reasons whilst the realizationusing server-client technologies can reduce costs for the ”cloud”-providing company [20]. The businessmodel analyses show, that cloud-based business models typically address natural persons as ”customersegments”, despite targeting in the B2B sector. For example, the pure provision and visualization of dataseems to be a successful value proposition for some market segments and applications. A special featureof cloud-based business models compared to more traditional business models without the cloud, seemsto be the opportunity to address the managers in a company who make the business decisions but usually

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do not get into direct contact with the products. Here, a cloud-based solution, which can be accessedeasily from multiple locations – also e.g. from the administrator’s office desk –, can provide an addedvalue for the customer. In the course of developing appropriate business models in the B2B sector, it isof major importance to pay attention, which roles with different competencies at the customer side areto be addressed (e.g. facility manager or CEO of a building management company). Furthermore, it isessential to clearly communicate the advantages and differences of the cloud-based solution comparedto more traditional offerings. In the consumer market, different roles (decision maker, user and sponsor)are combined in one natural person – the customer. In the B2B market, these roles are split onto at leastthree different natural persons in the customer organization. The persons all have different needs anddesires and thus require individual value propositions. B2B business models therefore need to provisionvalue propositions addressing all customer roles to be able to survive in the market. Cloud technologybrings a great advantage in this respect, as data can be accessed from anywhere, and the outcome of data-based services can be worked up differently for each role within a customer organization. Changing fromclassical software to cloud technology is often compared to outsourcing [17, 22]. However, in the sectorof industrial applications cloud computing will not replace existing solutions, but will rather introducenew functionality and indirectly along with this added value [20]. The added value in cloud-based B2Bofferings is thereby often delivered through additional services utilizing the data in the cloud. The cloud-technology acts as an enabler for new offerings [3] and only partly as the added value directly.s Thisindustrial study is limited in some aspects. First, it was assumed that all investigated business models aresuccessful and thus can be seen as role models for other industries moving towards cloud business. Forfuture studies it could also be of interest to identify and analyze failed business models, e.g. of productstaken from the market or from companies which went bankrupt. The accompanying business modelsmight provide further insights how B2B cloud business in the industrial sector works. Another constraintof the present study is that the business model canvases were created retrospectively and with an externalview based on existing business ideas. The external position of the authors, which to some extend alsomarked a competitor view, did not permit a validation of the retrospectively generated business modelanalyses with the original companies. Purely academic and independent research institutions might bein a better position for asking for a direct feedback on the business model analysis at the offering compa-nies, but, on the other hand, might lack the insight in the industrial environment and the deep understandof it. The small number of investigated cloud business cases is a further limitation of this study. Fu-ture studies should investigate a larger number of cases, despite the lack of B2B cloud business casesin the industrial environment. These studies may also focus on specific industry segments in contrastto the present study, which aimed at getting a broad overview of possible B2B cloud business models.Further research is necessary to develop industry-specific cloud B2B business models. For this purpose,available classification methods for cloud business models may be used [6, 4, 5]. Furthermore, someframeworks for the ground-up development of cloud business models are available [7, 23]. Based onthe analyses of existing cloud business models, future research may additionally look for generic cloudbusiness patterns. These can then be derived from successful businesses and applied to cloud offeringsin other industrial segments (Fig. 1).

6 Conclusion

In this industrial study a methodology to derive business models from B2B cloud offerings was intro-duced and used to analyze three exemplary cases of B2B cloud business models related to the industrialautomation domain. The major findings covered that B2B cloud business models differ from B2C cloudbusiness models, as e.g. in B2B customer organization roles are separated onto different individuals,whereas in the B2C market these roles are combined in one natural person. Cloud solution can thereby

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foster the acceptance of new services, as data can be easily stored, distributed and visualized for roleswithin an organization. The analyses also revealed, that B2B cloud business models are not only tobe seen as IT outsourcing, but that they can rather address previously unsolved customer concerns andneeds. From a technical perspective, this study showed, that some examined B2B offerings may not needcloud technology and can be realized using regular server-client approaches, but that a ”cloud” label cansupport the marketing and sales of the offering. Further research in this area may investigate B2B cloudbusiness models for specific industry segments in more detail as well as examine the possibility to de-rive patterns in B2B cloud business models to support the development of business models for new B2Bcloud offerings in the industrial environment.

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Author Biography

Martin W. Kruger studied Electrical Engineering and Information Technology atthe University of Karlsruhe (TH), Germany, and the University of Auckland, NewZealand. He received a PhD in biomedical engineering in 2012 from the KarlsruheInstitute of Technology (KIT), the successor of the University of Karlsruhe (TH). Dr.Krueger joined ABB Corporate Research in 2013 and his interests lie in businessmodel innovation, service science and Industrie 4.0.

Marcel Dix studied Computer Science at the Hochschule Mannheim, University ofApplied Sciences, Germany, and International Management at the FernhochschuleHamburg, University of Applied Sciences, Germany. He is working at ABB CorporateResearch Center Germany with research focus on Big Data and Cloud Technologies.

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Analysis of Cloud Business Models for the Industrial B2B Market