How Cloud Computing is Changing the Way Companies do CRM and Manage Knowledge

Abstract

In the past couple of years a lot has been published regarding Customer Relationship Management (CRM) and its implementation in large and medium sized companies.

For small to medium sized companies (SMEs), most CRM solutions are too expensive and such an expense cannot be justified to the stakeholders. However cloud computing has turned this situation around and these companies, and even specific departments in large multi-national companies, are implementing CRM solutions. Companies like Salesforce.com, SugarCRM, Microsoft Dynamics CRM and others realised the potential of this market sector and are quickly jumping on the chance of becoming the market leader.

Purpose - A lot of research has been performed on the benefits that CRM technologies can bring a company but the purpose of this study is to ascertain what advantages and disadvantages a cloud computing implementation of a customer relationship management (CRM) system has over a more traditional in-house implementation. Through the analysis of the differences between cloud, in-house, bespoke and package solutions and how these solutions are applying concepts in Information and Knowledge Management (KM) I hope to understand if current implementation methodologies are appropriate and adequate.

Outcomes and Findings – Findings of this research will include details on the status of KM CRM solutions, CRM methodologies, cloud computing and in-depth analysis of questionnaires and interviews. It will also include a recommendation based on the gaps identified in the methodologies, a CRM user profiling theory and technology comparison findings.

Practical Implications - Although the findings of this dissertation are highly conceptual, the results should prove that investing in research on Cloud Computing CRM solutions is valuable and areas such as user information profiling require further study. Additionally this dissertation raises outstanding questions on legal matters associated with these technologies.

Originality/Value - The concept of information user profiling based on KM theories and customer relationship management is new. The concept of business model impact on current CRM implementation methodologies is also unexplored since cloud computing technologies have only been introduced to the business market in the past decade. I will also cover the information ownership and distribution rights issues related to cloud based CRM solutions which have not currently been adequately discussed in the academic community.

1. Introduction

In this first chapter, the basis for the area of research is set. An introduction and general background are provided in order to clarify the topic to be discussed.

CRM technologies have gone through many advances in the past 10 years since vendors have been releasing products which are more usable and affordable to small to medium sized companies. These advances in the area are making it difficult for companies to succeed and gain that extra edge without a customised CRM system. A lot of companies, without even realizing it, already implement CRM techniques just by tracking their customers, recording their data and tracking customer interaction, even if it is done through a simple spreadsheet.

Many organisations rely on sales agents/people to sell their products and services. Truthful and accurate information sharing between the sales team and the organisation will benefit both since the conveyed information about the market, will enable better decision making. Additionally, it will allow for the organisation to improve the ability to tailor compensation to the sales agents through the analysis of their sales efforts. This is one of the main reasons why CRM solutions benefit not only the company but the employees as well.

To be able to compete in a difficult business market, organisations are trying to access new types of knowledge and capabilities (Jutla et al., 2001) and are therefore moving into an intensive knowledge seeking environment. These companies are becoming more dependent on customer knowledge to improve their objectives and long-term success (Bang et al., 2005; Bose and Sugumaran, 2003), and are using the knowledge derived from their CRM operations and other solutions such as Knowledge Management (KM) systems (Bose and Sugumaran, 2003). Cloud computing CRM solutions are quickly evolving to try to meet these new business requirements.

The implementation of several Salesforce integrations in projects for client organisations of Axispoint Solutions Ltd will serve as an aid to identify and obtain a detailed view on cloud computing solutions and how it is applied to the company’s business and information management structures. These projects will be analysed throughout the project lifecycle, from Discovery to Prioritization, Build, Test, Review and to the final Live delivery of the finished product.

1.1. Aims and Objectives

The aim of this research is to investigate how CRM implementations are changing with the arrival of new technologies such as Cloud Computing and SaaS, with particular focus on the Information Management issues that arise from these new implementation methodologies.

To achieve the aforementioned aim the following objectives were defined:

  1. Compare current CRM methodologies and assess their adaptability to cloud solutions.
  2. Ascertain the benefits and limitations of these implementations.
  3. Gain in-depth knowledge of cloud CRM implementations through my work placement and my role as a Salesforce CRM consultant.
  4. Examine the usage and implementation of different CRM solutions such as cloud, in-house, package and bespoke.
  5. Investigate the benefits that cloud computing and different CRM implementations provide from an Information and Knowledge management perspective.
  6. Investigate the current information ownership and legal issues raised by cloud solutions.

To achieve this the research questions we want to answer with this paper are as follows:

  1. How do CRM implementation methodologies adapt to new Cloud Computing technologies?
  2. How are information ownership and distribution rights managed by CRM systems?
  3. Is there a difference in the speed and flexibility of customisation of cloud based CRM solutions compared to in-house and bespoke compared to off the shelf?
  4. Is there a difference in the depth and nature of information and knowledge between the users of cloud based solutions and in-house solutions? And between off the shelf and bespoke packages?
  5. Can CRM users be categorised based on their data usage?
  6. Are CRM systems robust and reliable in their ability to restrict and grant access to data/information/knowledge to individuals and groups?

1.2. Research Approach

It was important to start the research by combining previous literature, common sense and my own experience with CRM and Cloud Computing. Additionally, due to the business nature of the topic I decided to use both questionnaires and interviews to gather qualitative and quantitative information from individuals and organisations.

A three-stage strategy was adopted, that combines quantitative and empirical data, based on two different questionnaires and complemented with expert interviews.

1.3. Research scope and limitations

Since CRM and Cloud Computing is a broad research subject it is important to define the scope of this research in order to provide a clear, objective and comprehensive discussion to the audience.

1.3.1. In scope

For the scope of this research, the definition of CRM should cover the major aspects of the CRM and its role in achieving its objectives. The definition considered most relevant in the scope of this dissertation is based on Payne (2004) Shang and Lin (2005) and Payne and Frow (2005) which defines CRM definition as: a strategic approach to integrate Process, People, and Technology to understand the organisation’s customers and create long term profitable relationships with these and improve stakeholder value.

There is a commonly accepted categorisation of CRM components that identifies four main categories: People, Business Culture, Process and Technology (Ali and Alshawi, 2003). For the scope of this research we will be concentrating on the technology aspect, however, it is accepted that all categories may influence the findings. Technology refers to the computing capacity that allows a company to obtain, collect, organise, store and use the data about the customer and it allows organisations to improve the relationship with their customers by providing a wider view of the customer behaviour (Thompson et al., 2006). As per this definition, it is important to include in this research the Information Management aspect of CRM technologies.

Additionally, this study will only cover the CRM technological functionalities that can be categorized in the six main CRM groups such as Sales Force Automation, Customer Service, Information and Knowledge Management, Customization, Analytics and Collaboration.

The scope will also be defined by the projects developed by Axispoint and the requirements and specifications defined during the Discovery and Prioritisation phases with the client organisations.

1.3.2. Out of scope / limitations

It is out of scope for this dissertation to experiment or perform implementations with any CRM tool since the objective is to analyse existing enterprise applications and user experience. The research will be done through questionnaires and interviews/case studies and this information will be used to compare and analyse current CRM tools available to the public. Due to the low frequency of hardcoded customizations in Cloud Computing CRM solutions, it is out of scope to further analyse these language based (usually in a mix between an HTML and XML) page implementations, customizations and enhancements.

It is important to note that it no commercially sensitive data will be included or discussed throughout this report. Whilst comparing implementation methodologies no consideration will be given to other factors governing the choice of implementation, i.e duration or difficulty of implementation. Systems implemented with the included methodologies will not be reviewed.

1.4. Dissertation Layout

This dissertation consists of seven sections: literature review, CRM implementation methodologies, research methodology, results and discussion, evaluation and CRM user profiling and conclusion. The literature review provides an in-depth overview of the chosen topic, the way it has been addressed and the necessary background information to aid the understanding of the research outcome. Many authors have used different definitions when referring to cloud computing trying, where possible, to define its meaning to present a common understanding on the topic. The objective of this project is to provide an in-depth view on CRM cloud computing solutions from an information and knowledge management perspective; therefore it was important to explore these topics thoroughly in the literature review.

To complete the analysis, this research will draw a correlation between information management and usage and how it can be associated to CRM user profiles. This correlation will be detailed in the evaluation and conclusion sections of this dissertation.

2. Literature Review

The aim for this chapter is to provide a summary of the relevant literature in the field with a specific focus on the critical points for this study. It will provide a logical presentation of the literature, by presenting facts and conclusions in a straight forward and succinct form.

The literature review will commence by defining the meaning of CRM and its meaning within an organisation. After defining the requirements, the literature review will proceed to define Cloud Computing, its benefits, challenges and criticisms, and Software as a Service (SaaS).

We will then proceed describe a high level view on different author defined methodologies which companies’ use to implement CRM solutions, in order to understand what the main factors that influence an organisation in choosing a solution over another are. However, for clarity purposes the CRM methodologies section will be presented as a separate chapter.

Further more will aim to present facts and arguments on the benefits and limitations that such technologies can achieve, and it will then conclude with an overview of the conclusions that have been reached.

2.1. Definition of CRM

Today’s society can be characterised by the fast changes both technological and consumer preference, which is highly reflected in the growth of competition between companies (Donnelly et al., 2000). Due to this, it is becoming even more important to provide a personalized customer service, which has led to small and big companies investing in Customer Relationship Management (CRM) (Berry, 2003; Beasty, 2005).

CRM practitioners have defined CRM in many different ways due to different influences (Zablah, Bellenger and Johnston, 2004) or, if considered, in a Marketing perspective (Bradshaw and Brash, 2001; Massey, Montoya-Weiss and Holcom, 2001). Massey, Montoya-Weiss and Holcom go beyond this definition and closely relate CRM with knowledge assets.

Payne (2004) Shang and Lin (2005) and Payne and Frow (2005) defined CRM as a strategic approach to integrate Process, People, and Technology. The objective of this approach is to gain understanding on an organisation’s customers to create long term profitable relationships and improve stakeholder value.

We can expand their approach and define CRM as a strategy for managing a company’s interaction with its prospects, clients and customers. It usually requires the usage of technology to support this strategy in order to manage and organise activities such as sales, marketing, customer service, knowledge management and content delivery among many others.

For this research purpose the definition that better applies to the process that we will be following is to define CRM as an interactive process built to generate the maximum profit by achieving a balance between business investments and customer satisfaction (Shaw and Reed, 1999).

The importance of the usage of Information Technologies (IT), which usually requires high monetary investments, associated with the market globalisation, technological development and competition increase has meant that CRM has usually been implemented, in its majority, by large corporations (Chalmeta, 2005).

2.1.1. Nature of CRM in an Organisation

CRM should be considered a company-wide strategy and not only a Sales or Marketing initiative. It should embrace all departments since when an implementation is successful and effective, the processes and technology employed, will improve profitability and reduce costs across the organisation.

CRM tools have been shown to help companies attain the following objectives:

All these benefits justify an investment in a CRM solution, but more importantly, they justify an investment in a customised solution that has been adapted to the organisation’s business model and processes.

Companies implement CRM in order to find new prospects, attract and win new customers, manage the relationship with current customers and reduce management, marketing and support costs. CRM emerged from a shift in a business way of thinking, when companies stopped focusing on transactions and started to concentrate on establishing, marketing and managing relationships with customers (Bose and Sugumaran, 2003). Another factor in this shift was when companies started to focus on the importance of customer retention instead of single sales (Parvatiyar and Sheth, 2000). Moreover, to increase customer retention, it was identified that companies needed to understand their customers better, and to do this, they would need to gain knowledge and better understanding through the information they have or could collect through their CRMs.

2.1.1.1. The Small and Medium Enterprise Reality

Current CRM business applications, such as SAP and Siebel, are complex to implement and expensive both to purchase and to maintain. They require expensive data centres, servers, storage, maintenance, data networks and most of the time they require a team of highly specialised and extremely expensive experts on site to build, configure, maintain and progressively improve the systems. When a customer requires a significant change in their business process, due to the complicated implementations, it sometimes takes months, and to wait for a specific alignment of the stars in the sky, to deploy the required software changes to Production.

When new versions of these business applications are launched sometimes it requires complicated upgrades to servers, other connected software and even office workstations which worked with the previous version but struggle or fall over with the new one because it requires a higher computation power. Not to mention the complicated process of training staff and convincing them to change the way they work.

For larger companies with a lot of money to spend some of these expenses are just a means to an end however for smaller companies, where the money is less abundant, the expense of CRM is not justifiable.

According to Beasty (2005) the Small and Medium Enterprises (SME ) have increased their CRM technology investments. Considering some of the specific SME characteristics, such as their scarce financial power and simple structure (Caldeira, 1998; Balbinot, 2007), it is believed that their CRM implementations are different when compared to a large enterprise implementation.

Due to this movement of SMEs acquiring CRM technologies, some CRM vendors have moved their attention to this new emerging market since, for example, it is believed that most of the companies in the United Kingdom (UK) are SMEs . Many CRM implementations fail at several levels, like lack of project effort or problems with the business automation (Bielski, 2004) and, as mentioned previously, SMEs do not have the financial leverage as other larger enterprises. Due to this factor, different solutions, with different pricing models that will fit into the enterprise budget and financial capability, needed to be explored.

So, how is Cloud Computing solving these problems and changing the market of the CRM solutions?

2.2. Definition of Cloud Computing

Before any research could be done it is important to understand the concept of Cloud Computing and how it applies to the business world.

For clarification purposes this section will aim to introduce the relevant terminology and concepts and is comprised of different subsections that will provide an overview on the typical Cloud Computing architecture, the business and service models and the business applications for this technology. It will also include an overview on the issues and benefits that companies should consider before implementing a Cloud CRM solution.

Cloud Computing predecessors have been around for a while and several authors have tried to define it (Vaquero et al., 2009) but the term started to become more widely used sometime in 2007 when IBM and Google announced a collaboration in Cloud Computing and after IBM launched “Blue Cloud” (IBM, 2007), a series of cloud computing offerings to allow distributed, globally accessible resources.

2.2.1. Re-defining a collection of defined concepts

Until now only a few scientific contributions have tried to define an accurate definition of cloud computing. Some authors have described it as a “collection of many old and few new concepts in several research fields like Service-Oriented Architectures (SOA), distributed and grid computing as well as virtualization” (Youseff et al., 2008). Youseff et al also state, in the same research paper about the Cloud Ontology, that “cloud computing can be considered a new computing paradigm that allows users to temporarily utilize computing infrastructure over the network, supplied as a service by the cloud-provider at possibly one or more levels of abstraction” (Youseff et al. 2008).

Others say that Cloud Computing refers to “both the applications delivered as services over the Internet and the hardware and systems software in the data centres that provide those services. The services themselves have long been referred to as Software as a Service (SaaS). The data centre hardware and software is what we will call a Cloud. When a Cloud is made available in a pay-as-you-go manner to the general public, we call it a Public Cloud; the service being sold is Utility Computing. We use the term Private Cloud to refer to internal data centres of a business or other organisation, not made available to the general public. Thus, Cloud Computing is the sum of SaaS and Utility Computing, but does not include Private Clouds” (Armbrust et al. 2009).

So there is a movement to see Cloud Computing not as a new term, but a collective definition that covers pre-existing computing concepts. Armbrust et al goes beyond this definition and expands the definition to new concepts being introduced in the cloud such as computing availability on demand, the elimination of a user commitment to acquire expensive computing resources and the usage of pay per use pricing model on short-term contracts (Armbrust et al. 2009). This view from Armbrust et al applies perfectly to the CRM solution market.

Vaquero et al. expands the definition provided by Armbrust by stating that “clouds are a large pool of easily usable and accessible virtualised resources (such as hardware, development platforms and/or services). These resources can be dynamically reconfigured to adjust to a variable load (scale), allowing also for an optimum resource utilisation. This pool of resources is typically exploited by a pay-per-use model in which guarantees are offered by the Infrastructure Provider by means of customised SLAs” (Vaquero et al. 2009).

The majority of Cloud Computing definitions have originated from service providers, consulting firms, market research companies such as Gartner and enterprise applications themselves. For example Marc Benioff, CEO of the on-demand cloud computing solution called Salesforce.com describes the Cloud Computing model as Multi-Tenant, Pay-as-you-go, Elastic and Real-time and he disagrees with the generic definition that has been applied to the Cloud. The debate on what can be defined as cloud computing is clearly demonstrated by Benioffs’ comments this summer at the Cloudforce conference in which he shown a slide titled "Beware of the False Cloud!" (Benioff, 2010) with the picture of Oracle Exadata which is a storage appliance, that is used to build private clouds.

Leimeister et al. performed a comparison between several authors that have provided definitions for Cloud Computing, such as Armbrust et al, Breiter/Behrendt, Briscoe/Marinos, Buyya, Foster et al., Gartner, Grossman/Gu, Gruman/Knorr, McFredries, Nurmi et al., Vaquero et al., Vykoukal et al., Wang et al., Weiss and Youseff et al. They have concluded that there is an underlying consent around features such as service, hardware, software, scalability, usage bond payment models and virtualization and internet/work.

For the purpose of this dissertation and in the scope of the chosen topic, we will define Cloud Computing as an Internet-based computing where resources, software and information are shared and provided on-demand, much like a utility, like electricity or water. It involves the provision of dynamically scalable or virtualized resources as a service, scalable on demand and priced on pay-per-use, over the Internet.

2.2.2. Architecture

Cloud Computing has a different architecture when compared to more traditional technologies and business solutions. It is composed of a front end, accessible to the end user of the business customer who purchased the licenses, usually used to access the required information or data. And it is also composed of a back end, usually referred to as the Cloud, where all the stored information is remotely stored in databases and servers.

The two ends of the architecture are connected through a network, usually the internet, to allow access to all users wherever they are in the world through a commonly used software technology like an HTTP browser.

For large companies, cloud computing technology eliminates the necessity to buy more hardware since new data could be accessed through their individual computers. Additionally, cloud computing does not require software installation, since the platform is easily available through the internet. This architecture allows them to make the transition to a modern trend: to make it mobile.

2.2.3. Cloud Business model

Cloud computing provides an affordable alternative to buying and installing an in-house software, where an organisation pays to obtain a business application according to their users, business and technological requirements and usage, by “renting” a space in a shared data centre being used by other companies. So, instead of having to take into consideration all the investments mentioned previously, a company can divide these expenses in small monthly instalments and since the solution runs in the cloud, it can be made available in a matter of days.

A major aspect of Cloud Computing is the interaction between the technological and the economic forces covered previously. Much like the iTunes Store pricing model where individuals can download one song instead of the whole album, CRM vendors are offering a different pricing model from the standard. This is where Cloud Computing comes in. Companies that cannot justify the IT investment of buying expensive servers and hardware can acquire only the necessary to allow them to use a CRM solution.

Cloud computing allows them to “rent” a service in a shared remote environment, scalable to their needs, therefore allowing companies to take advantage of a powerful tool like a CRM solution without having the associated hardware costs.

Cloud Computing does have its critics and not everyone thinks it is a strong business model. Chuck Goolsbee, one of the contributors for searchdatacenter.com, raises an important issue on compliance and regulation issues “A cloud is amorphous and indistinct. It is layer seven, abstracted from all the lower layers. You can't audit a cloud. It is virtual”. Goolsbee also defends his views against the Cloud business model by dissecting the financial issues related to demand and supply by stating that “Demand fluctuates, and unless you are going to charge usurious rates when demand comes in, you will burn cash at terrifying rates when demand is down”. He was referring to the layers defined in the International Standard Organisation for computer communication.

These are all valid points of view however; it is the responsibility of the company to take these into consideration when choosing a Cloud Computing application. This is why it is important to for a company to analyse its requirements such as the data that is going to be stored, the business workflows and processes and the risks and advantages before choosing a CRM technology.

The different CRM implementation methodologies will be reviewed in detail in chapter 3 when we analyse the different author defined methodologies and how they apply to today’s technologies.

2.2.4. Cloud Computing Service Models

The National Institute of Standards and Technology (NIST) defined Cloud Computing as a model to enable convenient, on-demand networks and remote access to computing resources, like servers, storage, application and services that allow quick provisioning and delivered with a low management and service effort. This definition can also be broken down into three service models:

Many different authors have classified Cloud Computing services (Kontio 2009, Reeves et al. 2009). For example, Wang et al. extends the common defined levels to include three additional services: Hardware-as-a-Service (HaaS), Software-as-a-Service (SaaS) and Data-as-a-Service (DaaS). These three services form PaaS (Wang et al. 2008).

Most Cloud Computing CRM Solutions are considered as SaaS services however some are a combination of these service models. Salesforce, for example, is a platform provider (AppExchange), an application provider (CRM) and it can also host its own infrastructure or partly source it from third party infrastructure providers.

2.2.4.1. Software as a Service (SaaS)

Software as a Service (SaaS), or software on demand, can be defined as a type of software that is deployed over the internet, in which a vendor or provider makes an application available to customers, usually through a subscription in a “pay as you go” model, on demand.

A CRM SaaS implementation is not guaranteed to be less costly than an on premise CRM alternative. Since SaaS provides a more evolutionary approach to functional enhancements it means that organisations can perform several iterations of their CRM implementations, customizing its functionality to their business process.

SaaS has been proven to be more efficient for dynamic organisations, where their business processes are constantly being adapted due to the ever changing market needs. For smaller organisations, where problems and processes are less complex, these on demand solutions are proven to be quicker to implement and cheaper to acquire.

SaaS was initially widely deployed for sales force automation and CRM and has since expanded to cover areas and business tasks such as human resource management, billing, invoicing, financials, content and document management, collaboration and service desk management.

Thus, the SaaS usage expansion, combined with the fact that SaaS has been evolving in the past decade and has become increasingly popular in the last 5 years, caused by an increase in demand of higher levels of functionality by customers, has caused a surge in the SaaS provider market.

2.2.5. Cloud computing business applications

Usually cloud computing providers make business applications available online that can be accessed by software like a web browser or a web service while the software and data are stored in servers controlled remotely by the provider.

These CRM applications are sold as subscriptions, where customers do not need to invest in the acquisition and maintenance of IT hardware and the subscription fees are much lower than the cost of purchasing the software.

These services and platforms are rapidly growing in popularity since they overcome some of the frustrations that most IT departments have to face, like long implementations, maintenance and upgrade projects for products or software packages with complicated integration and dependencies between applications. Cloud computing minimized the time spent on these activities and allows companies to focus on their core business activities.

While much research is being done on the technical aspects of Cloud Computing, many authors ignore the business perspective which has the potential to revolutionize traditional value chains and create new business models.

Some application providers like Amazon, Google, Microsoft, IBM and Salesforce have come forward as platform and infrastructure providers in the Cloud Computing market, which is still an emerging market with a lot of developments still to be made.

The following diagram depicts some examples of companies that are offering cloud services:

Companies offering Cloud services

Figure 2 - Companies that are offering Cloud services(Image used under Creative Commons from Sam Johnston)

2.2.6. Issues and concerns

The progress in cloud computing has brought forward two primary concerns: privacy and security. For cloud computing technology to be beneficial to all users, it is important that the platform is accessible to all users but remains a secure and private means of performing business on the internet. Its architecture provides remote access over the cloud, but the security and privacy should not only be inside the system in its internal sharing rules but outside as well.

2.2.6.1. Commonly identified security issues

Thinking a system is infallible

SaaS and PaaS (Platform as a Service) providers usually advertise their cloud services as more secure than most enterprise networks, however most systems are usually considered secure until proven otherwise. A good example of this was when Google’s Gmail service collapsed in Europe in February 2010 and the company was forced to issue an official apology to its customers. Another example was when Salesforce.com was the victim for a phishing attack in 2007, in which a staff member was to blame for a password leak.

The truth is, all systems have flaws, and cloud computing services are attracting a lot of attention from individuals with less than honest agendas due to their rich data and information storage. “The richer the pot of data, the more cloud service providers need to do to protect it” stated IDC research analyst David Bradshaw.

Understanding all the risks

Cloud users should be aware and understand the risks of data breaches. Cloud computing infrastructures advocate the idea of multi-tenancy and decoupling between hardware resources and applications. Companies and system administrators need to be vigilant, for example, on password policies and they should ensure that these are strong and there have been no breaches.

Some CRM tools are increasing their security procedures by implementing stronger password policies, further security checks such as limited IP access (to ensure that only computers inside the organisation are able to login into the system), complex security tokens to increase the security of external Application Programming Interface (API) connections, among other procedures.

Google, which is considered one of the world’s largest technology companies, has invested a lot of money into the cloud, and recognizes that one of its main factors for success is their security reputation. The company practices an in house security strategy, in which they apply security procedures to their processes, technologies and even people.

The Standards and jurisdiction gap

There aren’t a lot of security and data privacy specific standards in the cloud. The current status of cloud computing standards can be compared to where the recording industry was a couple of years ago, when it was trying to fight peer-to-peer file sharing with copyright laws. There is no current legislation that directly applies to the cloud and even after IBM, Cisco, SAP, EMC and several other leading technology companies announced in March 2010 that they had agreed on an “Open Cloud Manifesto”, there is a long way to turn these ideas into a legal framework.

The fact that neither Amazon.com, Google, Microsoft nor Salesforce agreed to be a part of the list of supporters suggests that an industry consensus might be difficult to reach. Some companies like Microsoft even accused IBM of trying to push their own private agenda.

Some current standards apply to Cloud Computing, such as the ISO23001, which is designed to provide foundations for third party audit and implements the Organisation for Economic Co-operation and Development (OECD) principles that govern the security of network and information systems. The auditing standard SAS-70 is also being used by cloud service providers.

Cloud computing not only impacts SAS-70 and Sarbanes-Oxley (SOX) compliance, but also Payment Card Industry Data Security Standards (PCI DSS), Gramm-Leach-Bliley (GLBA) and the Health Insurance Portability and Accountability Act (HIPAA). A good example of such impact is that, for example, encryption is necessary when transmitting HIPAA data on public networks. Since cloud computing, in theory, pushes data storage over the Internet, data should be stored in an encrypted format to comply with HIPAA. Additionally, extra measures such as non-disclosure agreements and background checks should be required for any users with access to this data.

Although standards and legislation are important, the most pressing issue is jurisdiction and local law. In most cases, users of cloud services are not aware of where their information is held, and data might be legally secure in one country and not in another. The European Union (EU) is trying to harmonise the data laws of its member states and to instate strict protection of privacy laws, however in America laws such as the US Patriot Act allow government and other agencies limitless powers to access information.

All these issues make jurisdiction an important factor for companies to consider when choosing cloud services. European concerns about the US laws led to the creation of the US Safe Harbor Privacy Principles, which provides European companies with some protection regarding US laws.

Security is often pointed about as a concern by companies, who are considering cloud computing but truth is, the model reduces the common causes of data breaches like the loss of a USB drive or a CD Rom. Employees no longer need to carry around all their company information with them and this increases security.

2.2.7. Understanding the benefits

Taking into consideration all the issues mentioned previously might be enough to scare any customer or organisation that is planning to move their business into the Cloud however some benefits should be measured against these risks.

All Cloud customers, for a particular solution, share one single infrastructure stack and one version of the software and then, only at a logical layer, are the customers separated. This alternative to a single-layer approach allows for customers to share resources and avoids costly individual installations, where customers own set of software needs to be periodically updated.

In a cloud solution when a service is upgraded, it is upgraded for all customers at the same time due to their multi-tenancy business model, and it does not require any involvement from the customers. These upgrades can be achieved without any significant system down time because some of these solutions hold a meta-layer, built on top of the physical infrastructure that manages how each application is supported, allowing for changes to be applied instantly. The customer retains access to the functionality whilst the infrastructure and software that manages it is abstract, performing functions such as back-ups, disaster recovery, performance tuning and other maintenance tasks, but all completely transparently.

Another advertised benefit is the disaster recovery service that is available with cloud solutions. Setting up virtual environments and then replicating them for disaster recovery services is costly for customers to implement themselves. The cloud CRM solution providers avoid this expense by replicating the whole infrastructure.

2.3. The CRM Information pyramid

CRM solutions are generally designed to implement the Information Management pyramid: collect data, transform it into information and to retrieve knowledge from this information. But how are users fitting into this scenario? And what if the nature of CRM could expand beyond its initial purpose of managing a customer’s company interaction?

The current CRM wave is expanding from its initial definition and branching out to areas such as Knowledge Management (KM), Customer Support and Content Management. Currently companies try to manage their internal knowledge and content by implementing software like Microsoft Sharepoint, which aims at sharing information inside the corporate environment, but CRM vendors are finally realizing the potential of the tools they are developing has and are starting to invest and expand their CRM service provisioning.

Bose and Sugumaran (2003) state that true CRM can be achieved only through the integration of KM which in result improves business processes and allows organisations to improve their visibility of the customer’s level of satisfaction, profitability and loyalty. These authors also point out that a simple and general framework for this integration does not exist.

2.3.1. The DIKW Hierarchy

The Data Information Knowledge Wisdom (DIKW) Hierarchy, also known as the "Wisdom Hierarchy", the "Knowledge Hierarchy", the "Information Hierarchy", or the "Knowledge Pyramid" (Rowley, 2007) , refers to a class of models (Zins, 2007) for representing relationships between data, information, knowledge, and wisdom. "Typically information is defined in terms of data, knowledge in terms of information, and wisdom in terms of knowledge" (Rowley, 2007).

The knowledge component of DIKW "is generally agreed to be an elusive concept which is difficult to define. Knowledge is typically defined with reference to information." (Rowley, Hartley 2006).

Zins suggested that knowledge is not the subject of study in information science, while Zeleny has suggested that to capture knowledge in symbolic form is to make it into information, i.e., that "All knowledge is tacit" (Zeleny 2005).

Knowledge can be defined as mix of experiences, values, contextual information, expert insight and intuition that creates an environment/framework to evaluate and incorporate new experiences and information.

2.3.2. Knowledge Flows in CRM

Many authors have researched into the relationship between Knowledge Management and CRM (Winer, 2001; Massey, Montoya-Weiss and Holcom, 2001; Romano and Fjermestad, 2003) and some academic contributions have even coined new terms such as ‘Customer Knowledge Management’ (CKM) or ‘Knowledge-enabled CRM’ (Gibbert, Leibold and Probst, 2002; Gebert, Geib, Kolbe and Brenner, 2003).

Dous et al. in 2005 defined CKM as “the utilisation of knowledge for, from and about customers in order to enhance the customer-relating capability of organisations” however it is only now, in 2010, that we start seeing the first CKM initiatives taking place in business applications, like Salesforce.com, where CRM vendors are taking advantage of the Cloud to finally bring these ideas forward.

Knowledge flows in CRM are seen as extremely complex since they are not very structured and can carry a large amount of knowledge (Eppler, Seifried and Röpnack, 1999). In a CRM context, the definition provided by Quintas, Lefrere and Jones in 1997 applies perfectly to this scenario since they define KM as the “process of managing knowledge to meet existing needs, to identify and exploit existing and acquired knowledge assets and to develop new opportunities”.

The DIKW pyramid can be closely related to the type of data, information and knowledge that can be collected, stored, aggregated and retrieved from an information system like a CRM. The following illustration shows how the customer’s location, usually saved in a CRM solution, can be extrapolated to information, knowledge and lastly wisdom.

Dous et al. distinguish three kinds of flows that summarise the KM requirements in a business: knowledge for, from and about customers. Their in dept research summarised previous research from several authors in areas such as the flow of knowledge from the company to its customers or prospects (Davenport and Klahr, 1998), the type of information being exchanged (Garcia-Murillo and Annabi, 2002) and the impact on customer satisfaction and company financial performance (Wang and Lo, 2004).

Dous et al. also reiterate the importance of the flow of knowledge from the customers to the company and innovation (Thomke and von Hippel, 2002; Gibbert, Leibold and Probst, 2002), appropriate feedback mechanisms (Garcia-Murillo and Annabi, 2002; Gibbert, Leibold and Probst, 2002) and importance of customer information (Reichheld and Schefter, 2000; Davenport, Harris and Kohli, 2001).

The analytical CKM framework by Dous et al. can be summarized in the following diagram.

Mazandarani et al. (2010) propose a set of KM critical factors and define a proposed model to show the relationship between KM critical factors and CRM. The model consists of a set of components categorized in two main sections: KM critical factors (Customer knowledge, Organisational Factors, and KM infrastructure) and CRM performance (tangible and intangible aspects). This model reiterates the importance of technology and suggests that technology is no longer seen solely as a knowledge extractor, but also contributes in the sharing of knowledge within the organisation (Mazandarani et al. 2010).

2.3.3. Customer Knowledge Management Challenges

In order to address customers’ needs, employees used information from different organisation departments that were gathered and aggregated by a specific team allocated to assist in information related tasks. After receiving the requested information, the employee had to organise it individually, and most of the time the information was not shared with other employees. To address this lack of information access and sharing, new knowledge platforms were created using web technologies which allowed for this information to be obtained more easily.

As the amount of content increased, caused by time and/or the company customer base expanding, the navigation structure became more spread out and difficult to manage. Due to the search limitations offered by this solution, some employees quickly return to using personal folders and even email to obtain the information they are looking for, instead of using the organisations shared knowledge base.

Additional problems related to converting documents to web-based formats also created issues and costs with the creation, formatting and publishing of online content.

All these issues contributed to the current issues such as Information Overload, the existence of too many platforms/systems/software in an organisation and the difficulty that is to drive good user adoption of new systems.

3. CRM implementation methodologies

In this chapter several CRM implementation methodologies will be assessed and compared and the limitations associated with the dissertation topic will be specified. Additionally the inadequacies will be identified and used to propose a new methodology.

The implementation of CRM technologies allowed an increase in competitiveness for many companies, which was mainly reflected in an increase in revenue and a decrease in operational costs (Chen e Popovich, 2003). These authors state that for a successful CRM implementation it is necessary to have the adequate technology and to have a good organisation of the company business processes and human resources. It allowed companies to achieve deeper re-structures, a more detailed organisation of their activity and to coordinate the relationships between the company resources (Caldeira, 1998).

Through CRM software solutions it is possible to store client data and analyse it to detect consumer patterns (through data mining), which allows not only to know the organisation customers better, but also to generate better business opportunities.

For some organisations, the biggest issue associated with a CRM implementation is the technological factor. However, the main reason for implementing a CRM solution is to gain an advantage for the customer and the organisation, and IT will only facilitate the implementation (Buttle, 2004). Buttle also states that not all CRM initiatives require high levels of IT investment, since its main objective is to manage the relationship with a customer. This can be achieved through changing the behaviour of human resources, training call-centre employees and focusing on the empathy created by sales people.

CRM can bring many benefits that, in order for them to be effective, require a deep analysis of all aspects of its implementation. It is important to understand the best way an organisation can do this, through the analysis of the methodologies of several authors in order to investigate how user profiling should be considered before choosing a CRM solution and methodology. It is important for us to analyse these methodologies to understand how companies tend to evaluate their requirements, and how their information knowledge management objectives are taken into account when implementing a CRM solution.

3.1. Winer’s Client Marketing Methodology

Winer (2001, p. 91) defined a “basic model, which contains a set of seven basic components: a database of customer activity; analysis of the database; given the analysis, decisions about which customers to target; tools for targeting the customers; how to build relationships with the targeted customers; privacy issues; and metrics for measuring the success of the CRM program.”

The first component consists of building a clients’. For clients who have already initiated their business activity, they should use their historic information to create a database of transactions, contacts, descriptive information for client segmentation and marketing information. The second component should analyse the information collected previously to define client segments and identify consumer patterns through data mining. The third component is used to perform client selection, whilst the forth component should segment the previous client pool to select the best approach to communicate with them. The fifth level is directly associated with loyalty programs and level six was created to ensure that the client privacy is respected. Finally, level seven is directly associated with monitoring and measuring the CRM implementation.

We can summarise this CRM process in respect of marketing into the following elements:

3.2. Urbanskiene’s Relationship Theoretical model

Urbanskiene et al. (2008) defined a model composed of seven stages: auditing of the current situation; client segmentation; database construction; human resource orientation; internal process organisation; choosing of the information technology; and investment definition.

These authors, after reviewing other methodologies of authors such as Winer (2001), Jason(2004), Popovich (2003), Reichheld (1996), Future Lab Business Consulting (2003), among many others, reiterate the importance of understanding the management and development of the relationship in customer relationship management. For Urbanskiene et al. in order to implement a CRM successfully “it is necessary to balance and integrate technologies, processes and people”.

3.3. The Ten Steps Framework

Jenkinson and Jacobs (2002) present a ten step framework to help companies deliver value to their clients with a CRM project. For them it is important that the CRM strategy be beneficial to the client, to the employees and to the organisation. The steps are: investment definition; optimise the customer relationship; build trust and reputation; creation of a relevant service; creation of enduring value; manage touch points; creativity development; measure and learn; technology selection; and last, but not least, stakeholder management.

This framework focuses its attention not only on customer satisfaction, but also on employee and stakeholder satisfaction. It does not emphasise the technology selection, as evidenced by the fact that this step is only performed at the end, since it is a framework designed to force companies to first define the investment they are willing to make and look at their internal processes before any implementation is considered.

3.4. Stig Jorgensen and Partners’ Skills method

Lindgreen presented a study in 2004 about the implementation of a method developed by a consultancy company, named Stig Jorgensen and Partners. This method incorporates hard skills (situation reports, analysis, strategy and implementation) and soft skills (management commitment, employee participation, loyalty development, among many others). The method is structured in eight different levels: commitment of the top level management; development or a status report; loyalty analysis; strategy construction; implementation; management development; employee involvement; and the evaluation of the process of loyalty development.

According to Lindgreen (2004), the capacity to generate loyalty from the company will determine of the investment in CRM will be profitable and successful. The success needs to be measured through several indicators, mainly the client retention indicator, the increase in the organisation’s client base and the evaluation on the level of recommendation from its clients.

3.5. Zablah et al. methodology

Zablah et al. (2004) define the specification of a relationship management strategy as the first step for a CRM implementation. This step should be followed by planning on how to build long lasting relationship with clients and selecting the most profitable set of clients. After these steps are performed, the company will be ready to define the marketing mix for each client, with the objective of maximizing client value and profit.

Zablah et al also reiterate the importance of guaranteeing that the internal processes are clearly defined and everyone in the organisation is aware and understands them. In the next step of this framework, the management should evaluate the current status of the organisations CRM capabilities to understand if it is possible to efficiently execute all the processes that were previously defined.

The last point of this framework is related to the monitoring and continuous improvement cycles in the implementation process, to check that the previously defined objectives are being met and to identify new business opportunities.

This framework can also be considered a perspective where CRM should be directly related to customer knowledge management (Lin et al. 2006; Zablah et al. 2004).

3.6. Curry and Kkolou’s Five Stage Model

Curry and Kkolou (2004) propose a CRM implementation model based on five stages: strategy definition; implementation (implantation); creation of a measuring system; description of the company plans; and applying the technology. For these authors, the CRM implementation starts with the strategy definition. To successfully implement the CRM it is necessary that the organisations strategy has the client as its main focus.

Curry and Kkolou (2004) suggest that this kind of strategy will influence the company’s human resources to orientate its objectives to deliver value to the client. They also defend that the top management needs to be the driving force who defines what it is expected from the organisation and all its elements.

3.7. CRM-Iris methodology

The CRM implementation methodology proposed by Chalmeta (2005), named IRIS, is composed by 9 steps: project management pre-requisites; definition of the company’s organisational framework; definition of the customer strategy; designing of the customer relationship definition system; creation of a process map; human resource management; construction of an information system; project implementation; and monitoring.

Chalmeta (2005) states that several success indicators need to be used to evaluate the success of the project, mainly to measure the improvement in the client value, and to confirm that the previously established dates are being met. Then most important aspects of the CRM for this implementation methodology are the definition of the customer strategy, re-engineering of customer facing business processes, human resources management, change management, improvement process and finally the computer system.

3.8. Damacena and Pedron’s Five Stage model

Damacena and Pedron (2004) propose a CRM implementation model based on a literature analysis, composed in five stages: planning and definition of the relationship model; client relationship process redesign; choosing the CRM tool; implementation of the chosen tool; evaluation of the results obtained through the CRM tool.

For a CRM project to be successful the following factors need to be taken into consideration: Relationship strategy definition, Client differentiation, Management support, Integration of the different company areas and departments, Organisational structure and culture review, Human resource training and profiling definition, Company process design and definition, Project Monitoring, Tool/technology definition, Database definition, Strategic alignment between IT and the organization and an appropriate IT investment.

3.9. Payne’s Strategic Framework

Payne (2005) proposes a framework composing five steps: strategy development; value creation; multichannel integration; information management; and progress evaluation. For this author, the strategy definition has two important sides: the companies and the clients.

To evaluate the success of this methodology Payne (2005) proposes that it is necessary to create analysis metrics in both the stakeholder and the client perspective. For the stakeholders it is important to detect if there was a reduction in costs, and the financial results related to the employees, clients and stakeholders.

Payne also defends that it is important to analyse the clients’ satisfaction, loyalty and the associated results. This way it is possible to verify the weak and the strong points of the CRM implementation and apply the necessary adoption and improvements.

3.10. Axispoint’s LEAP methodology

Axispoint Solutions Ltd implements a methodology named LEAP, which has been designed to be agile and adaptive to the client needs, by having a modular design. It is an evolutionary methodology since each module can be combined with others and can be used iteratively.

LEAP methodology by Axispoint

Figure 4 - LEAP methodology by Axispoint (Copyright Axispoint)

This methodology is based on the concept of the five segment wheel which includes a tiered approach of phases, modules and stages and each Module can also have iterations. For each Module, the Stage Diagram, Products, and Stages are given and it results in the delivery of several products. Each Module results in the delivery of several products which are passed on to subsequent Modules. The tasks to produce the products of the Module are broken into Stages.

This methodology follows the considerations outlined previously for SME CRM implementations, since it considers the importance of a Discovery phase which is designed to allow a project team to gather requirements and plan accordingly, taking into consideration the organisation’s size and their process. For smaller organisations the evolutionary approach, which can combine several iterations of the discovery cycle, allows for an implementation that fits well with the definition of a Cloud Computing CRM technology.

An important benefit of LEAP is that the Stakeholders are kept in the loop regarding progress throughout the project at the end of each module, which increases confidence in the delivery. This method allows that client staff observes the product development at every stage and allows for several iterations, sometimes invisible to the client, of a CRM implementation. It is relevant to point out that this methodology does not consider the fact that “the organisation’s management do not have enough time to concentrate on strategic planning” (Caldeira, 1998), which might hinder the development of the project, endangering the outcome and commitment of everyone involved.

3.11. Methodology comparison and discussion

The way that each author approaches the CRM adoption is influenced by its context and by the way they assign priorities to each phase of the methodology they have defined. For some authors, the implementation phase should be reached much earlier than others, like Chalmeta (2005) and Lindgreen (2004). For Chalmeta (2005), certain measures need to be performed before the implementation starts, to ensure its future success, like making the company employees aware of the upcoming changes in order to minimise the costs associated with the resistance to change and to motivate them. Lindgreen (2004) considers that the employee involvement in the CRM implementation process should be done after ensuring that the strategic bases are defined.

Some authors generalise their phases to have a much broader scope, since one of these phases can correspond to two phases in the methodology of another author. Again, the differences between Chalmeta (2005) proposed model and Lindgreen (2004) are a good example of this characteristic. Lindgreen (2004) considers that the first step for a successful CRM implementation is the top management commitment and its definition of the orientated vision of the process and, only at a later stage, the human resources are involved. For Chalmeta (2005), the commitment of the top management and the employee motivation so they can get involved in the process only starts in his requirement gathering phase which is revisited later.

Although there are many differences in the methodology construction for each author, it is possible to identify the main stages in all of them. Some authors however, can be distinguished by defining stages that these consider essential and no other author has included them in their methodology. A good example of this, is the fact that Winer (2001) was the only author (of the authors that were included in this research) to include the importance of ensuring privacy when collecting data from the client so that they can feel safe and to continue to collect information that will allow the company to serve the clients both more efficiently.

The following table (Table 1) summarises the position of each author in regards to an optimal CRM implementation. It presents a matrix that correlates each author’s position and the several phases of the methodologies. After reviewing the different characteristics of each author’s vision, the phases have been grouped so they can be compared more easily.

The phases have been divided in to three major categories for organisational purposes: (1) planning, (2) execution and (3) control. Firstly there is the need to define a plan of action (planning), secondly the need to execute all the tasks related to the implementation of the previously defined project (execution), and finally, to check if the process has run as planned, to make it possible to have future improvements (control).

Phase category

Phases

Winer’s Client Marketing Methodology

Urbanskiene’s Relationship Theoretical model

The Ten Steps Framework

Stig Jorgensen and Partners’ Skills method

Curry and Kkolou‘s Five Stage Model

CRM-Iris methodology

Zablah et al. methodology

Damacena and Pedron ‘s Five Stage model

Payne’s Strategic Framework

Planning

CRM definition

X

X

X

Status Audit

X

X

X

X

X

X

Strategy definition and client segmentation

X

X

X

X

X

X

X

X

X

Investment definition

X

X

Execution

Creation of the database

X

X

X

X

X

Relationship definition

X

X

X

X

X

X

X

Creation of the points of contact

X

X

X

X

Client experience evaluation

X

CRM capability evaluation

X

Organisation’s process

X

X

X

X

X

Human resource management

X

X

X

X

Choosing of the technology

X

X

X

X

X

X

X

CRM Implementation

X

X

X

X

Control

Monitoring and learning

X

X

X

X

X

X

X

Loyalty analysis

X

X

X

X

Table 1 – CRM Author methodology comparison

The Axispoint LEAP methodology has not been included in the above comparison since it is not CRM specific. It is however very similar to Payne’s proposed methodology since the CRM implementation starts with a status audit and concentrates heavily on building a solution and monitoring and learning from it.

3.11.1. Methodology considerations for SMEs

The CRM implementation should always be performed according to the organisation’s and the environment’s characteristics (Chang, 2004). For SMEs, these present some special considerations, such as:

As mentioned previously, many SMEs are investing in CRM (Beasty, 2005) however, many believe that they only need to invest in a CRM tool/technology solution and expect fast and sometimes miraculous results. A successful CRM implementation requires a specific planning that fits the company’s profile and time for it to reach the desired results (Berry, 2003).

3.12. Gaps in the methodologies

After analysing the literature regarding the CRM implementation and the understanding of the different phases defined by the authors it is clear that these methodologies are dated. They do not consider the new technology developments that the CRM business stream has seen in the past couple of years, such as Cloud Computing and SaaS, and they do not consider the academic research that is being done in information and KM associated with CRM systems.

These methodologies should not only concerns themselves with the business processes and the data they are storing, but about the actual information that is being stored, its usage, the rights of distribution, ownership and the knowledge that will be extracted from the system. Information technologies should be considered as enablers for CKM but the way that organisations adopt them, is considered a success factor for KM implementation (Chong, 2006). The existence of “technological and informational” infrastructures enables organisations to know and understand their customers much better (Shanks and Tay, 2001).

The reviewed methodologies do not detail solution characteristics that should be considered early in the CRM implementation methodology such as the type of delivery format and the type of service. Current CRM tools can be built or delivered to customers in several package formats such as in-house (bespoke) and off the shelf solutions. In house solutions are usually built by resources allocated to a specific CRM implementation project that has the objective of creating a customised CRM solution, whilst off-the-shelf CRM solutions are software packages of a pre-built and ready to roll out solution. Since off-the-shelf are pre-built CRM systems, although they are highly customizable, they might require some level of compromise between the client business process and the vendor’s solution.

Additionally, organisations should also take into consideration the type of service they require. Current solutions have different type of services available such as SaaS solutions, that allow customers to access an off the shelf solution hosted in the Cloud. These solutions, as mentioned before, usually have a different pricing model which sometimes makes them more accessible for SMEs and departments with a limited available budget.

Organisations with few limited IT resources should also take this into consideration to decide if an in-house built solution is justifiable since the current market holds a large variety of CRM solutions. On the other hand, organisations with complex business processes, highly sensitive data and data ownership concerns should consider implementing an in-house built CRM to satisfy their business needs.

3.13. Proposed CRM implementation methodology

A new generic methodology can be defined which should include the following stages: definition of the CRM vision; human resource management; situation audit; information analysis; database construction; strategy definition; definition of a client relationship policy; process organisation; implementation of the information systems; and monitoring and learning.

The inclusion of a new “Information analysis” stage is very important since it should force an organisation to understand its information requirements before starting a successful CRM implementation. It is crucial to understand the type of information that is going to be stored by the company, to understand the information ownership rights that might arise, to study the dept and nature of the information and the knowledge that will be stored in the system.

4. Research methodology

This chapter will describe the overview, strategy, purpose and methods used in this research. It will also detail the design and data collection process for the questionnaires and interviews.

  • The aim of this research is to investigate how CRM implementations are changing with the arrival of new technologies such as Cloud Computing and SaaS, with particular focus on the Information Management issues that arise from these implementations. In order to select and use the appropriate research methods, it was necessary to assess the aims and objectives of the research and take into particular consideration the research questions.

    In context of the overall research requirement, which is to try to create a valuable piece of knowledge that can be applied to a real world environment; the research approach that was adopted was an empirical approach. According to Denscombe (2003), empirical research is seeking the necessary information which can be measured and recorded. Therefore, this approach was used to conduct a direct study of the topic at hand and produce tangible results within a real world setting. Due to the business nature of the topic, it fitted best to try to incorporate the methods of questionnaires and interviews, which are considered classic methods of social science research to gather qualitative and quantitative information from individuals and organisations.

    4.1. Research overview

    Usually theory and conceptual frameworks are based on combining previous literature, common sense and experience (Eisenhardt 1989), however in this research, it also combined both a synthesis of already existing literature on CRM, Cloud Computing, SaaS, Information Management and Knowledge Management with several interactions with CRM professionals to obtain an in depth view on the subject.

    For this approach the Gummesson (2002) “interaction research” was used, which is a form of research in which “interaction and communication play a crucial role”. The sources for the field-based insights or interactions are based on in-depth interviews with experts using Cloud and non Cloud based applications.

    4.2. Strategy / Methods

    For the purpose of this research, as mentioned previously, a three-stage strategy was adopted, that combines quantitative and empirical data, based on questionnaires aimed at Cloud Computing CRM users and complemented by the usage of interviews. These interviews were used to better understand the results and gain inside knowledge on the practical applications of a CRM inside a corporate environment.

    The two questionnaires aimed to cover aspects as “who”, “how many” and “how much” (Yin, 2002), therefore representing the exploratory part of the research, allowing us to proceed to the third stage of the research which will include analysing and drawing the appropriate conclusions.

    The generic CRM questionnaire was sent only to LinkedIn and other CRM users, whilst the second questionnaire was send to Axispoint customers identified as Salesforce and/or CRM users. The second questionnaire was designed to obtain opinions on Salesforce since it is a cloud computing solution, its usage, and the overall customer experience and usage characteristics.

    The third stage consisted of expert interviews and research based approach, attempting to address the “how” and “why” of the research. For this stage, four case studies were collected. The investigation of case studies through expert interviews in order to draw conclusions follows the research methodology approach defined by Yin (Yin, 2002).

    4.2.1. Methods – advantages and limitations

    The advantage of using questionnaires is the quality and amount of quantitative data that can be retrieved since the responses are gathered in a standardised format. As an example, for the first questionnaire I was able to retrieve more than 130 answers from anonymous participants from all over the world which allowed me to draw conclusions.

    The drawbacks/limitations of using this research method is that the questionnaires are standardised so it was not possible to explain any questions that the participants might have misinterpreted. Also, it was not possible to ascertain whether the answers given were honest.

    The benefit of using expert interviews is the fact that I could explain any points that the participant might have misunderstood and that I could repeat the questions and rephrase them.

    A disadvantage for this method is the fact it took some time to complete. Also the people I wanted to interview were busy professionals, with limited time availability, and some of them lived abroad so some the interviews had to be conducted online. Online interviews have a high risk of the participant being distracted and I could not use visual cues.

    4.3. Questionnaire design

    Several aspects had to be considered when designing the questionnaires including:

    1. Objective: obtain an insight on the usage, user experience and CKM profile of different CRM technologies in a corporate environment;
    2. Language: English;
    3. Terminology: business and CRM related terminology. Since the chosen audience were corporate employees with CRM experience, the questionnaire contained terminology specific to these environments;
    4. Company size: Small to medium enterprise organisations for the Salesforce questionnaire and any size for the generic CRM questionnaire;
    5. Location demographic: Not specific to any geographic location.
    6. Audience roles: the questionnaire was aimed at CRM users that ranged from IT administrators, Sales and Marketing Users, Data Analysts to CEOs and Managing Directors.
    7. Audience CRM experience: All Salesforce questionnaire participants were chosen due to their close relationship with Axispoint and experience with CRM technologies. For the generic CRM questionnaire the objective was to retrieve an impartial sample of answers, so the audience was willing participants with CRM experience that were mostly contacted over Linkedin.com ;
    8. Audience IT experience: IT experience was not required for participants since most CRM solutions are designed for business users;
    9. Audience demographic location: this factor was ignored since the questionnaire was made available online and all audience members were invited over email and/or Linkedin.com;
    10. Audience English proficiency: all participants were considered proficient in English in order to understand the questionnaire;
    11. Questionnaire structure: the questionnaires were divided into several simple logical sections. The Salesforce questionnaire was segment into: introduction, CRM software identification, usage experience quantification, opinion and request for further contact. For the generic CRM questionnaire only one logical section was defined since a requirement of this questionnaire was to keep it simple and easy to answer;
    12. Completion Time: a very important factor is the availability of the audience to reply to survey questions. Most of the target audience members are very busy individuals with small amounts of free time. Given this, completing the questionnaire could not take more than 5 minutes.

    4.3.1. Generic CRM questionnaire

    The objective for this questionnaire was to answer the research questions and to obtain insight into the usage of CRM solutions in regards to the users Information and Knowledge Management (IKM) and CRM experience.

    This methodology provides numerical measurements and statistical predictability that can be representative of the total target population (Barson, 2003) and was used to obtain a more thorough understanding of the topic. It was performed over the internet by means of an online questionnaire and it was done on large sample sizes, on a random sample of CRM users on LinkedIn and the survey design was structured and close-ended. It is important to point out that is difficult to address specific research objective questions with this type of research method (National Cattlemen‘s Beef Association, 2001).

    The structure for the questionnaire on CRM was designed according to the research questions and information introduced in the theoretical foundation of this dissertation. The formulated questions can be summarised as follows:

    1. How many employees work for your company?
    2. Is your CRM solution a packaged software or written in-house?
    3. Is your CRM solution hosted on in-house server(s) or in the Cloud?
    4. When you have a new requirement, how easy is it to have your CRM modified?
    5. When you want to change your CRM, how quickly can modifications be made?
    6. Are you able to customise your CRM system to meet your exact requirements?
    7. Do you use your CRM system to correlate and aggregate the stored information?
    8. Do you use the aggregated information reports in conjunction with other information to draw conclusions or analyse them for patterns?
    9. Do you use aggregated information to make business decisions or modify processes?
    10. Are you satisfied that your CRM system is robust and reliable?
    11. How easily does your CRM solution allow you to grant and restrict access to data?
    12. Are you happy with your current CRM solution?

    4.3.2. Salesforce questionnaire

    This questionnaire was designed to obtain a more in dept view of Cloud Computing solutions and was sent to Axispoint’s employees and customers that were current Cloud CRM users. Due to the close relationship with the company, these users were available to answer more questions and to dedicate more time to an extended questionnaire. This method has proven crucial for this research since it allowed a more in-depth analysis into some questions that rose in the first questionnaire, to obtain results in a more specific environment and context (Cloud Computing users) and to focus on a business perspective, which is very important for the Cloud Computing CRM off the shelf business model.

    The structure for this questionnaire was designed to allow an in-depth view on cloud solutions. The Salesforce questionnaire questions can be summarised as follows:

    1. What is the size of your organisation?
    2. Are you a current Salesforce user?
    3. Please specify how many Salesforce users your organisation has?
    4. How long have you been a Salesforce user?
    5. Did you or your company have another CRM solution before Salesforce?
    6. Which CRM Solutions you have used? Please rate these solutions.
    7. Please rate your Salesforce experience
    8. What are the most useful functionalities in Salesforce?
    9. If given the choice, would you continue to use Salesforce in the future?
    10. Would you recommend Salesforce to others?
    11. Does your company use any Knowledge or Content Management technology?
    12. Please share any additional comments about your experience with Salesforce.

    4.3.3. Questionnaire data collection

    The two questionnaires were carried between August and November 2010, and distributed in two ways: individual emails were sent explaining the purpose of the research; and the questionnaires were advertised on LinkedIn and on other social networking platforms (such as Facebook and Twitter). All communication and questionnaire invites included a link to the online questionnaire made available through the SaaS survey builder named SurveyGizmo.

    About 170 answers were returned: 123 answers for the CRM questionnaire and 41 answers for the Salesforce only questionnaire.

    Table 2 illustrates and summarises the demographics and volumes of received answers:

    Questionnaire

    Number of replies

    Number of ignored answers [1]

    Number of accepted answers

    Source Countries

    Company size distribution [2]

    CRM questionnaire

    123

    1

    122

    Argentina, Australia, Belgium, Canada, China, Denmark, Egypt, France, Germany, Hong Kong , India,

    Ireland, Italy, Kuwait, Mexico, Netherlands, Norway, Pakistan, Peru, Portugal, Romania, Saudi Arabia,

    South Africa, Spain, Sweden, United Kingdom , United States

    0 – 50: 32%

    51 – 250: 14%

    251 – 1000: 17%

    1001 +: 37%

    Salesforce questionnaire

    41

    10

    31

    Canada, Germany, India, United Kingdom, United States

    1-4: 3.2%

    5-9: 3.2%

    10-19: 6.5%

    20-99: 41.9%

    100-499: 32.3%

    500-9,999: 12.9%

    Table 2 - Questionnaire sample characteristics

    Although the surveys answer sample size is not representative of the worldwide enterprise market, the results can be considered well-founded as they represent a good sample of results of the CRM market and were sufficient to retrieve information on the benefits and faults of current CRM solutions and their inherent characteristics.

    4.3.4. In-depth / Expert Interviews

    For the purpose of this research a semi-structured interview was chosen, as defined by Senger and Österle’s case study method (Senger and Österle, 2002) based on the following business engineering principles:

    • Defining the old situation and the underlying problem;
    • Defining the solution and the proposed implementation project;
    • Specifying the solution after implementation and the associated costs and benefits.

    This technique might also be considered market research, which is the gathering and evaluating of data about consumers preferences for products and services, aimed at smaller sample sizes with fewer than 30 members. It contains more open answer questions in a more interview style and a well-know selected sample universe. Meaning, for this research, the sample members were not selected at random.

    Market research can be defined and segmented in many different ways; however we used the Qualitative definition provided by Mariampolski, in which he states that it is a group of methods and techniques for documenting and understanding attitudes and behaviours (Mariampolski, 2001). It is closely associated with anthropology and social sciences and in data collection this method relies on the environment and behavioural observations through unstructured and semi-structured questions and is usually exploratory, so it is very useful to obtain insight into questions that have not been clearly defined.

    The end interview questions can be summarised as:

    • CRM challenges: which issues were solved by implementing the solution;
    • Relevant CRM aspects: which approach was employed to improve the products and services;
    • Performance outcome: what were the tangible results;
    • Performance outcome: what are the intangible results;
    • Benefits: specification of overall benefits obtained by comparison of the company situation before and after the CRM implementation.

    The following table provides a brief summary on the selected experts for the interviews:

    Interview ID

    Company Size

    Customer Company Size

    Implemented CRM Solution

    Hosting

    Type of Solution

    Interview 1

    500-9999

    100-499

    Microsoft

    Cloud

    Package software

    Interview 2

    20-99

    10000+

    Salesforce

    Cloud

    Package software

    Interview 3

    20-99

    500-9999

    .Net/SQL

    In-House

    Bespoke

    Interview 4

    500-9999

    100-499

    Siebel

    In-House

    Package software

    Table 3 - In-depth interviews sample characteristics

    To clarify and elaborate on each case study, some interviews addressed more specific subjects in order to reconcile with each specific company requirement. This was achieved by performing further enquiries and addressing each expert experience as an individual study subject.

    4.3.4.1. Interview structure

    Each in-depth interview was organised into the following sections:

    Problem definition: This section was defined to describe the issue in the organisation and what and who was involved in defining it and resolving it. The objective was to define the problem and provide insight on why CRM was chosen to solve the proposed issue.

    Problem analysis: Defined how the information collection for the data analysis was performed. It aimed to specify the process that was used to extract information from the data. Usually this is mostly done by the organisation before choosing to implement a CRM system however the objective was to ascertain the experts view and experience.

    Implemented Solution: This section was defined to ascertain if other solutions were considered before the implementation phase, what was the main issue to be solved, whether the proposed solution met with the customer requirements and what were the steps that were taken. The objective here was to define which methodology was followed and attempt to associate it with the author defined methodologies identified in section 3.

    4.3.4.2. Interview data analysis

    For the case study and interview analysis, two different methods of analysis (Yin, 2002) were used:

    Within-case analysis

    • The objective was to build an explanation of the case study through a deduction and induction cycle. The validity of each study case was confirmed with the interviewed subject, through their review of the recorded data. All data was kept to ensure the proper evidence was saved;
    • Due to the emphasis on deduction, for the within-case analysis, is to explore existing or newly constructed theory, the results that are retrieved are dependent on the theoretical research context. It was very important to clearly present this theory in order to provide insight into it.
    • For the induction cycle, while the aim of this approach is to conduct research before any theoretical framework is used, in reality it might be difficult to achieve. To minimise this risk, the work placement with Axispoint was very valuable since it provided the opportunity to not only to conduct research on Cloud Computing and CRM solutions, but to actually gain valuable practical experiencing on the subject.

    Cross-case analysis of the data

    • This type of analysis was used to compare and examine the similarities between the interview answers. The objective of this analysis was to detect patterns, trends and find the common issues that play important roles in current CRM implementations.

    5. Results and discussion

    This chapter will present a summary of the collected results, obtained after a quality and statistical validation check (this process is detailed in the appendices) and will describe some of the conclusions that were reached.

    The following information, represented in written, tabular and graphical form illustrates the findings of the data gathered via the research methods detailed in the previous section.

    A large proportion of the collected questionnaire answers are qualitative however a summary of the significant patterns and observations will be provided. The research started with an overall look into current CRM usage and personal experience from several CRM professionals around the world. From the answers that were gathered a generic picture started to take shape.

    Pre-findings assumptions:

    • As companies increase in size, the allocated job/roles get more specific and the CRM users stop having an overall view of what is going on.
    • Not everyone understand the concept of the cloud: most cloud definitions are being divulged by vendors and market research companies who might have their own agenda. Since there is no universally agreed definition, although there is a lot of research being done in this area, some solutions are being marketed as cloud to take advantage of the virtualization trend in the market.
    • Most CRM users are not technical since most tools are designed to be used outside an IT environment; therefore the collected sample answers included both technical and non technical views.
    • In smaller sized companies, roles might overlap and CRM users might need a wider access to the system to be able to perform their day to day roles.
    • Security concerns in regards to the type of information stored and access to it depends directly on the type of business or industry the company is part of.

    5.1. CRM questionnaire results

    The first step of the research and result analysis was performed on the CRM questionnaire results. This data was analysed firstly in a statistical approach to validate the retrieved results and this detailed information is attached in appendices F and G. After the statistical results were confirmed the data was then analysed, transformed and summarised in the results presented below.

    5.1.1. Sample company size

    CRM Quest. - Sample company size distribution

    Graph 1 - CRM Quest. - Sample company size distribution

    Although the company size might appear irrelevant to the research, it is in fact very important due to the nature of cloud solutions and their target market. Most of the sample answers were from professionals working in large sized companies, which is a market sector that has been using CRM technologies since the 1980s. Not surprisingly, considering the new market tendencies, the sample also showed that SMEs are investing in these solutions as well. The company distribution was used as a basis of comparison and pattern detection to allow us to have some insight on which technologies are being used by each size grouping of companies.

    5.1.2. CRM solution sample characteristics

    CRM Quest. - Sample company size distribution

    Graph 2 - CRM Quest. - Solution versus Company Size analysis

    CRM Quest. - Sample company size distribution

    Graph 3 - CRM Quest. - Hosting versus company size analysis

    Due to the complexity of CRM solutions and high IT investment required to implement in-house, it is expected that a high amount of companies would use packaged software solutions. Surprisingly, a considerable percentage of responders are using solutions in the cloud. As a consequence of the different cloud computing definitions and the confusion in this research area, where most definitions are being provided by vendors, it is believed that although some users think they are using a cloud solution, they are merely remotely accessing their solution, hosted on company servers, through the internet.

    CRM Quest. - Sample company size distribution

    Graph 4 - CRM Quest. - Tool type and hosting distribution

    CRM Quest. - Sample company size distribution

    Graph 5 - CRM Quest. - Type versus hosting comparison

    5.1.3. New requirements modification difficulty level

    CRM Quest. - Sample company size distribution

    Graph 6 - CRM Quest. - Company size versus new requirements difficulty

    The analysis of the metrics related to the requirements difficulty by company size shows that larger sized companies are more difficult to introduce new changes to. This is probably related to the complexity of the business processes, increased security measures and change management processes, amongst other factors.

    CRM Quest. - Sample company size distribution

    Graph 7 - CRM Quest. - Solution Type versus new requirements introduction difficulty

    It can be seen from the sample results presented previously that regardless of the type of CRM solution being used, it does not affect the level of difficulty to introduce new requirements being reported by the users. It appears however that solutions hosted in the cloud make this change easier.

    Similarly to what was noted above regarding the introduction of new requirements, the responses indicated that both built in-house and packaged solutions are difficult to change. Cloud solutions appear to be easier to modify.

    As seen previously in the introduction of new requirements, the answers indicate that it is difficult to make changes to CRM solutions in larger sized companies. Close to 4% of the results indicated they did not know the level of difficulty associated with making changes to the system, but this is normal since the sample group includes technical and non-technical users or they might not been involved in this process.

    5.1.4. Modification speed

    CRM Quest. - Sample company size distribution

    Graph 8 - CRM Quest. - Company size versus new requirements introduction speed

    Smaller organisations using packaged software results appear to be register that it is quicker to perform changes to the system, whilst larger organisations changes are slower to implement. Again, this can be associated with the complexity of the companies’ internal policies and processes.

    CRM Quest. - Sample company size distribution

    Graph 9 - CRM Quest. - Solution Type versus speed of changes

    The speed of making changes can also be correlated with the adopted CRM solutions as seen in the graph presented previously. It appears that it is quicker to perform changes in solutions hosted in the Cloud.

    5.1.5. Customisation level limitation

    CRM Quest. - Sample company size distribution

    Graph 10 - CRM Quest. - Company size versus CRM customization to meet requirements

    CRM Quest. - Sample company size distribution

    Graph 11 - CRM Quest. - Solution type versus CRM customization to meet requirements

    In regards to whether users were able to customise their CRM system to meet exact requirements, or if there were any limitations stopping them from obtaining information, workflows or requirements that were needed, most package users raised some kind of concern. There is a higher percentage of cloud users stating that their CRM could be customized most of time or even always.

    5.1.6. Information Management and reporting

    CRM Quest. - Sample company size distribution

    Graph 12 - CRM Quest. Aggregation/correlation of Information & Knowledge management usage

    As seen above, 75% of the surveyed users use the CRM system to correlate and aggregate the information held into reports and graphs for management use. Furthermore, 90 out of 119 users stated that they used this information in conjunction with other information to draw conclusions or analyse them for patterns.

    CRM Quest. - Sample company size distribution

    Graph 13 - CRM Quest. - Type of solution compared with the CRM IKM usage

    It should be noted that for smaller sized companies there appears to be a high percentage of users who do not use their CRM solution to correlate and aggregate the information held into reports or graphs for management use.

    Thus, the users who answered yes in the previous question were asked if they used the aggregated information reports in conjunction with other information to draw conclusions and analyse them for patterns. The objective of this question was to ascertain if users were actually aiming to collect knowledge.

    From the above information we can conclude that Cloud users are more inclined to use their solution for reporting and information management purposes.

    5.1.7. Information aggregation and knowledge creation

    It was important to understand out how many users that stated that they aggregated information for management reporting, actually used this information for other purposes. The following graph summarises the results retrieved after asking the users if they used the aggregated information to make business decisions and/or modify processes or if it is simply used for reporting:

    CRM Quest. - Sample company size distribution

    Graph 14 - CRM Quest. - Information knowledge and wisdom usage in the CRM system

    Presenting the above results in a different format shows us an interesting pattern:

    CRM Quest. - Sample company size distribution

    Graph 15 - CRM Quest. - IKM usage for in-house hosted solutions

    CRM Quest. - Sample company size distribution

    Graph 16 - CRM Quest. - IKM usage for Cloud hosted solutions

    The users were also asked if they used the collected aggregated information to make business decisions or modify processes, or if the information was merely used for reporting purposes.

    CRM Quest. - Sample company size distribution

    Graph 17 - CRM Quest. - Information to Knowledge and Wisdom impact

    This question allowed us to analyse that most Cloud users or the companies they worked for were using the knowledge obtained to create wisdom and to adapt/correct business processes.

    5.1.8. Data privacy and restrictions

    The CRM users were asked to rate/grade their CRM solution in regards to data access and privacy i.e.; how difficult it was for them to grant and restrict access to their data.

    CRM Quest. - Sample company size distribution

    Graph 18 - CRM Quest. - Type of Solution versus data privacy implementation

    It is interesting to note that written in house applications appear to have a greater level of difficulty whilst packaged software solutions, both in Cloud and on in house servers, allow easier changes that to be made by users to grant and restrict access to data.

    5.1.9. Robustness and reliability

    CRM Quest. - Sample company size distribution

    Graph 19 - CRM Quest. - Solution Robustness and reliability by company size

    From these results there appears not to exist a relationship between the robustness and reliability of a CRM solution and the company size.

    CRM Quest. - Sample company size distribution

    Graph 20 - CRM Quest. - Solution Robustness and reliability by type of solution

    However, when comparing the above results with the type of solution used, there was a higher percentage of packaged software Cloud users that believe they do not have an issue with their solution. These users have more confidence in packaged cloud solutions.

    5.1.10. Satisfaction

    CRM Quest. - Sample company size distribution

    Graph 21 - CRM Quest. - User satisfaction by company Size

    Most sample answers demonstrate that users are satisfied with their CRM solution, with medium sized companies (251-1000 employees) having the highest percentage of in satisfaction.

    The next step was to try to ascertain if factors like the type of solution and the type of hosting affect the level of satisfaction recorded in the questionnaires.

    CRM Quest. - Sample company size distribution

    Graph 22 - CRM Quest. - User Satisfaction by type of CRM solution

    As shown in the previous graph, a high percentage of users with written in-house CRM solutions hosted on in-house server(s) were not satisfied with their solution. Additionally there are a high percentage of users of in-house hosted solutions who are not satisfied, with more than 20% of the answers, which is very low compared to less than 5% of the total number of unsatisfied users of cloud based solutions.

    We can clearly see that packaged users are happier with their solutions than written in-house users and Cloud users are happier than in-house server based solution users.

    5.2. Salesforce sample answers

    Taking a detailed look at the input retrieved on the generic CRM usage, a more specific questionnaire was sent and sample answers were collected from current Salesforce.com users, a well known Cloud Computing CRM solution.

    5.2.1. Organisation size distribution

    CRM Quest. - Sample company size distribution

    Graph 23 - Salesforce Quest. - Company Size distribution

    Most of the answers were from professionals working in small sized companies, in contrast to the CRM questionnaire.

    5.2.2. Salesforce usage experience

    About 40% of the users have been Salesforce users for 1 to 4 years which means that in the majority of users are fairly new to Salesforce or even CRM and cloud computing. This fact cannot be proven since most of the answers were collected from Axispoint customer contacts, gathered from recent projects that have taken place between 2009 and 2010, which does not cover the full extent of the Salesforce customer base.

    5.2.3. CRM solution experience and comparison

    CRM Quest. - Sample company size distribution

    Graph 24 - Salesforce Quest. - Previous CRM solution experience

    The distribution between users that either did or did not have any contact with other CRM technologies before implementing Salesforce is fairly well balanced. More than 50% of users stated that their company owned different CRM solutions previous to implementing Salesforce as shown below as:

    CRM Quest. - Sample company size distribution

    Graph 25 - Salesforce Quest. - Alternative CRM solutions

    Users identified Act! has being the most used CRM tool, with 25.7% of the total answers, Oracle Siebel CRM with 20.5%, Oracle CRM On Demand with 15.4 and Microsoft Dynamics CRM with 18% of the votes, the remaining 20.5% were distributed between other solutions or not identified by the users.

    Additionally, users were asked to rate each solution by a series of business parameters. In overall, Cloud solutions such as Salesforce, Microsoft Dynamics and Act! were given higher ratings.

    CRM Quest. - Sample company size distribution

    Graph 26 - Salesforce Quest. - CRM solutions rating comparison by business criteria

    Due to the limited number of results and the missing data for solutions like SAP and Siebel, no definitive conclusions can be reached. However, for the data we have collected we can see that Salesforce, Microsoft Dynamics, Oracle CRM, Act! and Sage are clearly rated better in most categories than other alternative solutions and therefore it appears that these solutions are considered better by the surveyed users.

    CRM Quest. - Sample company size distribution

    Graph 27 - Salesforce Quest. - CRM solutions total ratings for all business criteria

    5.2.4. Salesforce usage metrics

    Most Salesforce users, with an overwhelming 96.6% of the answers, confirmed that the usage of Salesforce has improved the data quality and management inside their organisation. 62.1% stated that it improved their customer service and support, 58.6% stated that this solution has increased customer satisfaction, 86.2% stated it improved their analytics capability and 79.3% stated that it has reduced sales, marketing and other operational costs. Other metrics were retrieved, summarised in the following graph:

    CRM Quest. - Sample company size distribution

    Graph 28 - Salesforce Quest. - Salesforce.com usage metrics and ratings

    The most eye catching statistic is the value associated with the data quality and management. The obvious question to ask here is: is this associated with Salesforce only or with SaaS/Cloud computing CRM solutions?

    To try to ascertain and answer the above question, the users were asked to identify the most useful functionalities in the system, in which they identified the Real-Time and Historical Analytics, Sales Force Automation, Business Process Controls, Marketing Automation and the Application Environment (the AppExchange ).

    CRM Quest. - Sample company size distribution

    Graph 29 - Salesforce Quest. - Salesforce.com favourite functionalities

    Most users did not choose options such as the Data Model Customisation, Content Management or Case and Knowledge Management. We can conclude that the customisation and Information and Knowledge Management (IKM) management side of Salesforce is still not seen as a strong advantage when using this cloud solution.

    5.2.5. Knowledge management solution

    Another interesting result was obtained when the users were asked if their current company used any knowledge and content management solution.

    CRM Quest. - Sample company size distribution

    Graph 30 - Salesforce Quest. - Knowledge Management Solutions

    Most users identified Sharepoint, Intranet, Shared Folders and Databases, with only 14.6% of users stating they used the Salesforce native CRM Knowledge functionality.

    5.2.6. User satisfaction

    CRM Quest. - Sample company size distribution

    Graph 31 - Salesforce Quest. - Salesforce.com user satisfaction by company size

    The majority of users stated they were satisfied with their cloud computing solution, would continue to use Salesforce and would recommend it to others. There is no detectable pattern between user satisfaction and the company size.

    5.3. Interview analysis

    In order to obtain a more detailed input on specific CRM implementations, four CRM experts, experienced in implementing CRM solutions in several clients were contacted. The aim of these short interviews was mostly to understand how these implementations were conducted.

    Most of the collected answers were for solutions implemented in organisations with higher than 100 employees, with 50% of answers for 10.000 plus sized organisations. Most solutions were implemented with packaged software (75% of answers); with only one user stating that he used a bespoke solution. Half of all collected answers were using Cloud solutions and the other half in-house server hosted solutions.

    CRM Quest. - Sample company size distribution

    Graph 32 - Interview - Solution type and hosting

    The following table summarises the sample of collected answers in regards to the type of solution, the issues the implementation was aiming to solve, the chosen methodologies and the number of implementation cycles:

    Interview 1

    Solution

    Microsoft

    Solution Type

    Packaged software solution – Cloud

    Which issues were you aiming to solve?

    Customer Insight

    Did you use any specific methodology for choosing the CRM technology/solution?

    CMMI

    Did you use any project management methodology?

    Scrum

    One implementation cycle or different phases/separate smaller projects?

    One implementation

    Interview 2

    Solution

    Siebel

    Solution Type

    Packaged software solution -

    In-House servers

    Which issues were you aiming to solve?

    Lack of formal processes, lack of centralised view on Customers, Architectural restructuring, SFA, Customer Segmentation and Targeting, Call Centre Optimization

    Did you use any specific methodology for choosing the CRM technology/solution?

    Out of the solution providers, this is the one we figured most appropriate for the customer size, customer number subscribers and our own experience.

    Did you use any project management methodology?

    Company methodology

    One implementation cycle or different phases/separate smaller projects?

    Different Phases/Projects

    Interview 3

    Solution

    Customer Relationship Portal built in .NET, ETL in, PL/SQL and Microstrategy

    Solution Type

    Bespoke (custom-made) solution - In-House servers

    Which issues were you aiming to solve?

    Revenue assurance component in order to compare the customers pricing matrix and the customer revenue.

    Did you use any specific methodology for choosing the CRM technology/solution?

    Company objective was to re-use already internally available technologies since they already owned a big IT infrastructure and an existing Intranet portal

    Did you use any project management methodology?

    Prince2 methodology

    One implementation cycle or different phases/separate smaller projects?

    Different Phases/Projects

    Interview 4

    Solution

    Salesforce.com

    Solution Type

    Packaged software solution – Cloud

    Which issues were you aiming to solve?

    Too many databases, Management reporting, Lack of a centralised customer knowledge DB, Customer targeting/insight, unable to see how business units and clients relate to one another.

    Did you use any specific methodology for choosing the CRM technology/solution?

    No, customer had bought Salesforce.com and wanted a customisation

    Did you use any project management methodology?

    Agille Company Methodology

    One implementation cycle or different phases/separate smaller projects?

    One implementation

    Table 4 - Expert interview summary - solution and implementation details

    An interesting set of information was collected from the questions presented in the next set of results. The experts were asked if they considered the customers information and knowledge management requirements before choosing a solution and before the implementation was started.

    Interview 1

    Technology

    Microsoft

    Did you consider the customers information or knowledge management requirements before choosing the solution?

    Yes

    And before the implementation started?

    Yes

    What were the tangible results?

    Reduced costs, market & customer share

    What were the intangible results?

    Customer satisfaction, customer loyalty

    Interview 2

    Technology

    Siebel

    Did you consider the customers information or knowledge management requirements before choosing the solution?

    Yes

    And before the implementation started?

    Yes

    What were the tangible results?

    Customer market share is now around 80% of the market and has more than 18 million subscribers

    What were the intangible results?

    Easier launching of new products / services, increased retention of subscribers, less time in touch points (Call Centre, Shops)

    Interview 3

    Technology

    Customer Relationship Portal built in .NET, ETL in, PL/SQL and Microstrategy

    Did you consider the customers information or knowledge management requirements before choosing the solution?

    No

    And before the implementation started?

    Yes

    What were the tangible results?

    customer share and net sales

    What were the intangible results?

    Innovation and competitiveness

    Interview 4

    Technology

    Salesforce.com

    Did you consider the customers information or knowledge management requirements before choosing the solution?

    No

    And before the implementation started?

    Yes

    What were the tangible results?

    Net profit and sales, reduced costs, customer share, etc

    What were the intangible results?

    Customer Satisfaction, service and quality improvement

    Table 5 - Expert interview summary - IKM considerations

    These results were interesting since they show that some implementations did not consider the customers information and knowledge management requirements before proposing a solution, but they always consider these requirements before the implementation is started.

    The fact that the information and knowledge management requirements are not being considered before a solution is proposed introduces a limitation to the customers that are using a packaged solution since they are forced to adapt their requirements to the selected technology solution.

    Amongst the several methodologies pointed out as being used to select the CRM solution, such as the CMMI (Capability Maturity Model Integration), a solution provider selection based on consultant experience, or an implementation based on an existing customer acquisition, none of the people interviewed have used a specific CRM implementation methodology.

    6. Evaluation and CRM User Profiling

    This chapter contains an analysis of the data presented in the previous chapter. Conclusions will be drawn and based on the definitions in the literature review the research questions will be answered.

    The information collected from the questionnaires and the expert interviews allowed for an in depth view on the way users are interacting with CRM technologies and to answer some of the proposed research questions.

    6.1. Information Ownership and distribution rights

    Some research is being done around the benefits of cloud computing and the availability of cloud hosted solutions, but the truly important questions are not being answered, or maybe even asked: Who owns the information you put up in the Cloud? How is this information being stored? Who has access to it? What laws are applied to Cloud Computing?

    Much like when we go to a supermarket and use our Tesco or Nectar Card and our purchases are registered and analysed to perform targeted marketing campaigns, or when we go into an Apple store and when we swipe of credit or debit card and the employee tells us he has our email, home address and our name on their system, when is stored information dangerous?

    In most interviews there was no mention of the customer’s data protection. This factor was not considered at any point during each CRM implementation. Either the organisations are not worried where their data resides or this is not a factor that has been explained to them.

    The conclusion is that this topic is a very complicated question that can only be answered in a dissertation paper of its own. Chapter 2.2.6 discussed this topic in detail however, due to the very recent nature of this subject; the information available is still very limited.

    6.2. The gap in current CRM implementation methodologies

    The next research question I set out to answer was: how do CRM implementation methodologies adapt to new Cloud Computing technologies? I believe that this research proves that current methodologies do not take these new technologies into consideration.

    As seen in section 5.3, the interviews show that amongst only half of the studied CRM implementations considered the organisation´s knowledge management requirements before choosing the CRM solution. This proves that the implementation’s methodologies require the users to adapt their requirements to the chosen solution. This will force the organisation to adapt its processes to what the solution has to offer.

    If a chosen solution does not provide an environment that allows for a rich DIKW interaction and the company has users that require a high degree of knowledge retrieval, it may force the organisation and/or users to use other software tools which may lower the CRM solutions adoption rate.

    The identified gaps specified in section 3.12 can be summarised as follows:

    1. The methodologies do not take into consideration new business models/recent technologies – a business model such as pay-per-use, which has become available through Cloud Computing, should be considered for organisations that require or prefer this alternative. The methodologies should include a feasibility phase that considers these options against a customer’s requirements and investment needs and limitations.
    2. Reviewed methodologies do not consider KM requirements - although a lot of authors prioritise the building of the database and to understand the organisations information needs, they do not take into consideration the benefits that should arise from an appropriate DIKW perspective.

    Although the CRM solutions mentioned and used throughout this dissertation and work experience are starting to implement IKM solutions such as Salesforce’s Knowledge module, which is mostly aimed at organising internal and external customer facing information, they do not implement any type of IKM profiling techniques. Reports and dashboards are built to display information and show or hide information dependant on the user security profile, but they do not adapt the information displayed to a user’s requirements.

    6.3. Can CRM users be categorised based on data usage?

    All CRM users can be profiled in accordance with their interaction with the system and the data, information and knowledge it holds. Although some CRMs are highly customisable, it seems likely that the next big step will be to create intelligent user profiling. Adaptable user profiling that hides and shows information according to a user’s role/profile and information requirements. If a user is looking into a specific set of data in order to obtain knowledge, it makes sense to advise him that a specific report is available or to create an intelligent automatic report with one a click of a button.

    This is currently already available in similar formats, such as data mining which allows a user to drill into the lower levels of an information structure. The same solution but in the opposite direction should be implemented, taking advantage of the Cloud information and already available online resources.

    For example, taking into consideration the Salesforce.com experience I obtained through my internship placement, when a user is at a report level the only way of intersecting the displayed information with external information is to export the report and do this comparison outside the system.

    If the system could allow and advise for external information to be brought into the same report, according to the users profile or behaviour, as for example, the system would recognise a specific string pattern for a postcode in a customer list, and decided to cross reference this information with an external postcode database (grouping the displayed users by areas and the company’s area of action). Thus, completing and allowing for intelligent reporting and knowledge management to be available through the CRM. This possible CRM future might raise concerns over data privacy.

    6.3.1. CRM User Profiling

    Most users would just label themselves as CRM users, in an information and knowledge perspective they can be profiled and their behaviour can be closely correlated to the usage or the role they perform within the system.

    Taking into consideration the DIKW hierarchy defined in chapter , these users can be associated to two different characteristics:

    • Information seeking behaviour - are the users consuming what is in the CRM system?
    • DIKW pyramid placement – are the users working with Data, Info or Knowledge?

    From the information collected on the questionnaires it is possible to group users as being non consumers (who do not use the system to correlate and aggregate data or information into reports or graphs) or consumers. A consumer user can also be defined or named as a manager since these users will require data or information management skills to be able to perform the required aggregation and correlation.

    Aggregation and correlation of data from the CRM system will allow for the data to be transformed into information and enable the users who have identified that they use this information to make business decision and/or modify business processes. The information can be transformed into knowledge and even wisdom. Therefore, the Knowledge flow in CRM, as discussed in chapter 2.3.2, can be clearly identified in the user’s usage of the system, and these users can be profiled and associated with the DIKW pyramid.

    A user can be profiled as a consumer and a manager, and can be placed across the whole range of the DIKW pyramid. Though this is possible, a user who has behaviours from both information seeking profiles, Consumer and Manager, can be labelled solely as a Manager profile since this is considered a parent profile.

    The same cannot be said about their DIKW assignment (where you can place a usage in regards to Data, Information, Knowledge or Wisdom) since a user will usually need the previous level of the pyramid to reach a higher level, therefore these levels can be defined as correlated but separate in terms of user profiling. The following diagram attempts to map this relationship and the different excising profiles:

    Although the Wisdom level of the DIKW pyramid is represented above, it was left out from the CRM User Profiling since not a lot of users will fall into this category. Usually users on the Knowledge level will perform the Wisdom role, since this wisdom usually will require action being taken by other teams in the organisation.

    We can identify the following CRM User Profiles:

    • Data Consumers
    • Information Consumers
    • Knowledge Consumers
    • Data Managers
    • Information Managers
    • Knowledge Managers

    Based on my CRM experience and the nature of Cloud computing I believe that Force.com is a good example of a dynamic CRM solution that could be used to implement the proposed User Profiling theory due to its metadata-driven architecture. This architecture delivers scalability and customisation for on-demand multi-tenant applications since everything exposed to developers and users is internally represented as metadata, where information such as user access privileges, tenant specific customizations and business logic exists only in a UDD (Force.com’s Universal Data Dictionary).

    Illustration 6- Force.com’s metadata-driven architecture (Copyright © 2008, Salesforce.com, Inc.)

    The architecture allows for the user experience to be customised, therefore making it possible to create an intelligent user profiling system. The user characteristics/profiles can be stored in the UDD and the runtime application generator can interpret the stored information and adapt the tenant-specific screens.

    Depending on the user profile, the number of rows a user can access and other data related restrictions and filters stored in the UDD, the system should return Tenant and User specific screens. For example, if a user is labelled as a Knowledge Manager he will require a different User Interface (UI) and access to an appropriate set of stored data/information/knowledge to be able to perform specific aggregations and correlations.

    6.4. Speed and flexibility of different CRM solutions

    With this research I wanted to know if there was a difference in the speed and flexibility of customisation between cloud based CRM and in-house solutions and between bespoke and off the shelf packages.

    Despite the research and conclusions obtained in this study demonstrated that SMEs are using package and cloud based CRM solutions and appear to be happier with them, it is difficult to draw a correlation between cloud computing and the user’s level of satisfaction. Factors such as whether these companies are happy since they now have access to tools they were not using before, or whether these solutions are more easily adaptable to their simple business processes (when compared to large sized organisations) need to be considered before jumping to conclusions.

    As seen on the results displayed in section 5.1.10 it is clear that users prefer package software solutions to those written in-house. Additionally, the highest levels of dissatisfaction were reported by users of in-house hosted solutions but we can only speculate on the reason for this. From the conversations I conducted with experts in this area it appears that users and organisations consider remote and mobile access a very important user satisfaction factor. For example, in the UK, where working from home is becoming more usual, having access to a business application remotely is crucial and an important advantage.

    6.5. The information and knowledge difference based on the chosen CRM

    Close to 75% of the surveyed users use the CRM system to correlate and aggregate the information held into reports and graphs for management use and most of these users were packaged software Cloud users. We cannot conclude there is a different in the nature of information stored in the different types of solutions. It does appear that users have more confidence in packaged cloud solutions in comparison with bespoke solutions.

    The customisation and IKM side of Salesforce is still not seen as a strong advantage when using cloud solutions. Salesforce and other vendors are however strongly betting on these functionalities. Salesforce already has Knowledge module and it will launch a Force.com Database solution in 2011, where data is stored in objects and it allows developers to integrate the database and build applications in many languages, like Java, C#, Ruby or PHP, run them on platforms, like Force.com, VMforce, Amazon EC2 or Google AppEngine and securely access the data through standards based APIs.

    The Salomann et al. (2006) research article points to a justification for the lack of KM investment and adoption, stating that “firms may refrain from KM initiatives in CRM due to difficulty in visualizing the immediate benefits and short-term pay-offs of such projects”. Additionally it appears that KM is seen as a term with a negative connotation within an organisation and that this affects investment decisions (Salomann et al., 2006).

    Additionally, companies should analyse how a solution can allow them to move vertically within the DIKW pyramid in order to action changes that are originated from the lower levels of the pyramid. Regardless of the methodology used, it is important to consider the information requirements before choosing the CRM solution.

    6.6. Restricting and granting access to Data/ Information and Knowledge

    The last outstanding question in this research was to find out whether CRM systems are robust and reliable in their ability of restrict and grant access to Data, Information and Knowledge to individuals and groups.

    The information gathered is not enough to form an opinion and a correlation between the type of solution and its ability to restrict and grant access to stored data or information. From the collected answers it appears that in-house built bespoke applications have a greater level of difficulty when compared to package software solutions. However, we can only speculate at the reason for these results.

    7. Conclusion

    In this final chapter we present a conclusion and summary of the findings in the previous chapter with the aim of answering the research questions. The suggestions for future research will also be discussed.

    We have seen that a successfully implemented CRM is able to capture customer preferences, desires and their knowledge, which can be a very high benefit to an organisation (Romano, 2003). Chen and Li in 2006 stated that with the help of KM and CRM organisations can create new ideas and provide new and improved services.

    The objective of this dissertation was to answer the questions raised with regards to CRM and Cloud Computing technologies. After following the research methodology, several conclusions were reached.

    We can conclude that with regard to the question of information ownership and distribution rights on cloud CRM solutions, I was unable to reach any concrete conclusions. The area is a complicated one that requires more investigation. I believe that the fact that Cloud Computing is a fairly recent technology means that there is not a lot of information and research.

    With regards to the speed and flexibility of customisation of cloud based CRM solutions compared to in-house and bespoke compared to off the shelf, we can only conclude that SMEs are using package and cloud solutions and appear to be happier with them. The reasons behind these results are difficult to ascertain since they are particular to each organisation.

    In addition to these results, it appears that in-house built bespoke applications are more difficult to restrict and grant access to data which can be a security risk.

    Two important gaps in CRM implementation methodologies were identified which prevent organisations from considering KM and cloud computing technology advances when implementing a CRM solution.

    Additionally, the benefits derived from an adequate DIKW and KM implementation should be considered a good investment since, as stated by Liew (2008) “Knowledge-based customer relationship management is the highest sophistication of customer service as it deals with long term effects like building customer loyalty and value over the lifetime of the customer”.

    We have also discussed the categorisation of CRM users based on their data usage and their DIKW pyramid positioning as Consumers or Managers. A CRM User profiling categorisation is useful since it allows for a customisation and tailoring of the CRM environment to the users' needs.

    7.1. Methodology error

    The research methodology selected started off with a very specific Salesforce.com perspective, which I, after a nudge in the right direction by my supervisors, realised was not the optimal way of starting off my research. A more generic view of CRM was needed in order to understand how and who was using hosted and cloud computing solutions, so the methodology was modified and the scope was widened and in the end I think it had successful results.

    This research had a large impact for me both personally and professionally. Personally because it involved a large time investment for the past six months whilst I was working full time as a Salesforce Consultant and professionally, it allowed me to better understand a CRM user’s behaviour, to understand the surprisingly large proportion of CRM users who use the cloud and to obtain in depth knowledge of these users behaviour and usage of their CRM systems.

    References

    • Ahronovitz, M. et al. (2010), Cloud Computing Use Cases White Paper Version 4, [online], Available: http://opencloudmanifesto.org/Cloud_Computing_Use_Cases_Whitepaper-4_0.pdf [25 August 2010]
    • Amazon, (N.A). Amazon Elastic Compute Cloud EC2. Available: http://www.amazon.com/gp/browse.html?node=201590011 [Accessed 20 August 2010]
    • Amazon (2010). Amazon elastic compute cloud (Amazon EC2). Available at: http://aws.amazon.com/ec2/ [28 August 2010]
    • Ali, M., Alshawi, S. (2003). Investigating the Impact of Cross-culture on CRM Implementation: A Comparative Study. [online] Available: http://www.iseing.org/emcis/EMCIS2005/pdfs/EMCIS05-Alshawi.pdf [30 August 2010]
    • Armbrust, M., Fox, A., Griffith, R. et al. (2009). Above the Clouds: A Berkeley View of Cloud Computing. Berkeley, University of California. Available: http://www.eecs.berkeley.edu/Pubs/TechRpts/2009/EECS-2009-28.pdf [10 September 2010]
    • Bose, R., Sugumaran, V. (2003). Application of Knowledge Management Technology in Customer Relationship Management. Knowledge and Process Management, 10, pp. 3 – 17.
    • Bradshaw, D., Brash, C. (2001). Managing customer relationships in the e-business world: how to personalise computer relationships for increased profitability. International Journal of Retail & Distribution Management, vol. 29, no. 11/12, pp. 520.
    • Bueren, A., Schierholz, R., Kolbe, L. M., & Brenner, W. (2005). Improving performance of customer-processes with knowledge management. Business Process Management Journal, 11(5), pp. 573-588.
    • Berry, D. (2003). CRM for the small to medium enterprise – king-sized CRM on a bite sized budget. Customer [email protected] solutions, 21, 11; pg.56-59.
    • Beasty, C. (August 2005). SMB Are Upping tech Spending. Destination CRM [online] Available: http://www.destinationcrm.com/Articles/Columns-Departments/Insight/SMBs-Are-Upping-Tech-Spending-43031.aspx [23 September 2010]
    • Buttle, F. (2004). Customer relationship Management: Concepts and tools. Oxford. Elsevier Butterworth-Heinemann.
    • Caldeira, M. (1998). Understanding the adoption and use of information systems / information technology in small and medium-sized Manufacturing enterprises: a study in Portuguese industry. School of Management, Cranfield.
    • Carr, N. (2008). The Big Switch: Rewiring the World, from Edison to Google. New York: W.W. Norton & Company.
    • Chalmeta, R. (2005). Methodology for customer relationship management. Grupo integracion Y Re-ingenieria de Sistemas (IRIS), Universitat Jaume I, The Journal of Systems and Software, 79; p.1015-1024.
    • Chang, J., (2004). CRM at any size. SMM - Sales and Marketing Management. Sales & Marketing Management. Volume 156, issue 8; pp. 30-35.
    • Chen, Y., Li, L. (2006). Deriving information from CRM for knowledge management: a note on a commercial bank. Systems Research and Behavioural Science, pp. 141-146.
    • Chen, I. J., Popovich, K. (2003). Understanding Customer relationship management (CRM): People, process and technology. Business Process Management Journal, Vol. 9 No. 5 pp. 672-688.
    • Curry, A., Kkolou, E. (2004). Evaluating CRM to contribute to TQM improvement – a cross-case comparison. The TQM Magazine; 16, 5; pp.314.
    • Damacena, C., Pedron, C. D. (2004). Estratégia de CRM: O desafio da implantação. Anais do Congresso Anual de Tecnologia de Informação – CATI 2004 – FGV – EAESP.
    • Dholakia, N. Bang, J., Dholakia, R. R. (2005). CRM, KDD and Relationship Marketing: Requisite Trio for Sustainable E-Marketing. In Contemporary Research in E-Marketing. Volume 1. Idea Group Publishing.
    • Donnelly et al., (2000). Administração: Princípios de Gestão Empresarial. 10th Edition. McGrawHill.
    • Dous et al. (2005). Knowledge Management Capabilities in CRM: Making Knowledge For, From and About Customers Work. Proceedings of the Eleventh Americas Conference on Information Systems, Omaha, NE, USA
    • Eppler, M. J., Seifried, P. M., Röpnack, A. (1999). Improving knowledge intensive processes through an enterprise knowledge medium. SIGCPR, pp. 222-230.
    • García-Murillo, M., Annabi, H. (2002). Customer Knowledge Management. Journal of the Operational Research Society, Vol. 53 No. 8.
    • Gebert, H., Geib, M., Kolbe, L. M. and Brenner, W. (2003). Knowledge enabled Customer Relationship Management. Journal of Knowledge Management, 7, 5, pp. 107-123. Gibbert, M., Leibold, M. and Probst, G. (2002). Five styles of customer knowledge management, and how smart companies use them to create value. European Management Journal 20 (5), pp. 459
    • Google. (2010a). GOOGLE Apps. Available: http://www.google.com/apps/business/index.html [28 August 2010]
    • Google. (2010b). Google App Engine. Available: http://code.google.com/appengine [27 August 2010]
    • Goolsbee, C. (31 December 2008). Don't buy cloud computing hype: Business model will evaporate, SearchDataCenter.com. Available: http://searchdatacenter.techtarget.com/news/1343864/Dont-buy-cloud-computing-hype-Business-model-will-evaporate [16 August 2010]
    • Heiser, J., Nicolett, M. (2008). Accessing the Security Risks of Cloud Computing. Gartner, Inc., Stamford, CT.
    • IBM (2007). Google and IBM Announced University Initiative to Address Internet-Scale Computing Challenges. Available: http://www.03.ibm.com/press/us/en/pressrelease/22414.wss [31 August 2010]
    • Jenkinson, A., Jacobs, M. (2002). The IDM Guide to CRM Mastery. Published by Institute of Direct Marketing, Teddington, Middlesex, United Kingdom.
    • Jutla, D. Craig, J., Bodorik, P. (2001). Enabling and Measuring Electronic Customer Relationship Management Readiness. Paper presented at the 34th Hawaii International Conference on System Sciences, Hawaii.
    • Khalilabad, H. N. Mazandarani, O. N. Sentosa, I., Piaralal, S. K. (2010). The Impact of Knowledge Management on Customer Relationship Management. 2010 International Conference on Business and Economics Research (ICBER)
    • Kontio, M. (2009). Architectural manifesto: An introduction to the possibilities (and risks) of cloud computing. Available: http://www.ibm.com/developerworks/library/ar-archman10/ [24 August 2010]
    • Leach, J. (20 March 2008). The Rise of Service Oriented IT and the Birth of Infrastructure as a Service. Available: http://advice.cio.com/jim_leach/the_rise_of_service_oriented_it_and_the_birth_of_infrastructure_as_a_service [12 September 2010]
    • Leimeister et al. (2010) The Business Perspective of Cloud Computing: Actors, Roles, and Value Networks. Proceedings of 18th European Conference on Information Systems (ECIS), Available: http://home.in.tum.de/~riedlc/res/LeimeisterEtAl2010-preprint.pdf [16 August 2010]
    • Liew, C.-B.A. (2008). Strategic integration of knowledge management and customer relationship management. Journal of Knowledge Management, 12(4), p.131-146. Available: http://www.emeraldinsight.com/10.1108/13673270810884309 [16 October 2010]
    • Livny, M. (1988). Condor: High Throughput Computing. Available at: http://www.cs.wisc.edu/condor/ [20 August 2010]
    • Lohr, S. (8 October 2007). Google and I.B.M. Join in Cloud Computing Research. Available:http://www.nytimes.com/2007/10/08/technology/08cloud.html?r=1&ei=5088&en=92a8c77c354521ba&ex=1349582400&oref=slogin&partner=rssnyt&emc=rss&pagewanted=print [31 August 2010]
    • Massey, A. P., Montoya-Weiss, M., Holcom, K. (2001). Reengineering the Customer Relationship: Leveraging Knowledge Assets at IBM. Decision Support Systems, 32 (2), 155-170.
    • Mell, P., Grance, T. (2009). The NIST Definition of Cloud Computing. Version 15, National Institute of Standards and Technology, Gaithersburg. Available: http://csrc.nist.gov/groups/SNS/cloud-computing/ [10 September 2010]
    • Naone, E. (18 September 2007). Computer in the Cloud. Technology, Review, MIT. Available at: http://www.technologyreview.com/computing/19397/?a=f [25 August 2010]
    • Parvatiyar, A., Sheth, J. N. (2000). The Domain and Conceptual Foundations of Relationship Marketing, In: Handbook of Relationship Marketing. Sage Publications, Thousand Oaks, pp. 3-38.
    • Payne, A. (2006). Handbook of CRM: Achieving Excellence in Customer Relationship Management. Butterworth-Heinemann Publications: Elsevier, Oxford.
    • Payne, A., Frow, P. (2004). The role of multichannel integration in customer relationship management. Industrial Marketing Management. Cranfield School of Management, Cranfield University, Cranfield, Bedford.
    • Payne, A., Frow, P. (2004). A Strategic Framework for Customer Relationship Management. Journal of Marketing, [online] Vol. 69 (October 2005), American Marketing Association, pp. 167–176. Available: http://www.atypon-link.com/AMA/doi/abs/10.1509/jmkg.2005.69.4.167 [15 October 2010].
    • Pettey, C. (20 October 2009). Gartner Identifies the Top 10 Strategic Technologies for 2010. Gartner.com. Available: http://www.gartner.com/it/page.jsp?id=1210613 [16 August 2010]
    • Pettey, C. (22 June 2010). Gartner Says Worldwide Cloud Services Market to Surpass $68 Billion in 2010’. Available: http://www.gartner.com/it/page.jsp?id=1389313 [16 August 2010]
    • Private Consortium. (2009). Open Cloud Computing Manifesto. Available: http://www.opencloudmanifesto.org/ [27 August 2010]
    • Quintas, P., Lefrere, P., Jones, G. (1997). Knowledge Management: a Strategic Agenda, in: Long Range Planning. Vol. 30, No. 3, pp. 385-391.
    • Reeves, D., Blum, D.,Watson, R. (2009). Cloud Computing: Transforming IT Midvale. Burton Group.
    • Romano, N. C., Jr., Fjermestad, J.. (2003). Electronic Commerce Customer Relationship Management: A Research Agenda. Information Technology and Management, 4(2-3), 233 - 258.
    • Rowley, J. (2007). The wisdom hierarchy: representations of the DIKW hierarchy. Journal of Information Science 33: 163–180, Available: http://jis.sagepub.com/cgi/content/abstract/33/2/163 (CILIP Member or Athens sign in required or pay per article) [02 September 2010]
    • Rowley, J., Richard, H. (2006). Organizing Knowledge: An Introduction to Managing Access to Information. Ashgate Publishing, Ltd. pp. 5–6, Available: http://books.google.com/books?id=cZlYmQrnTMwC&lpg=PR17&ots=HNp63KXews&dq=Organizing%20Knowledge%3A%20An%20Introduction%20to%20Managing%20Access%20to%20Information&lr&pg=PR17#v=onepage&q&f=false [15 August 2010]
    • Salesforce.com Inc (1999). Salesforce Customer Relationships Management (CRM) system. Available: http://www.salesforce.com/ [Daily between May 2010 and January 2011]
    • Salesforce.com Inc (2007). Apex Code: The World’s First On-Demand Programming Language. Available: http://wiki.developerforce.com/images/7/7e/Apex_Code_WP.pdf [28 August 2010]
    • Shang, S., Lin, Jai-Sheng. (2005). A Model for Understanding the Market-orientation Effects of CRM on the Organisational Processes. Proceedings of the Eleventh Americas Conference on Information Systems, Omaha, NE, USA.
    • Shaw, R., Reed, D. (1999). Measuring and valuing customer relationships: How to develop the measures that drive profitable CRM strategies. Business Intelligence, London.
    • Saloman, H., Dous, M., Kolbe, L., Brenner, W..(2006). Advancing CRM Initiatives with Knowledge Management. Journal of Information Science and Technology (JIST) 3(2) 2006. The Information Institute. Available: http://www.jist.info/volumes/vol3/vol3is2/vol3no2-2.pdf [20 October 2010]
    • Vaquero, L., M. Rodero-Merino, L., Caceres, J., Lindner, M. (2009). A Break in the Clouds: Towards a Cloud Definition, Telefonica Investigacion y Desarrollo and SAP Research. Madrid, Spain and Belfast, UK. ACM SIGCOMM Computer Communication Review, Volume 39, Available: http://ccr.sigcomm.org/online/files/p50-v39n1l-vaqueroA.pdf [16 August 2010]
    • Virtual Computing Laboratory (2004). VCL, College of Engineering (COE) and the Office of Information Technology (OIT), Available: http://vcl.ncsu.edu [25 August 2010]
    • Wikipedia (2008). Cloud Computing. Available: http://en.wikipedia.org/wiki/Cloud_computing [25 August 2010]
    • Wikipedia (2010). Salesforce.com Available: http://en.wikipedia.org/wiki/Salesforce.com [30 August 2010]
    • Winer, R.S. (2001). A Framework for Customer Relationship Management. California Management Review, 43, 89–105, Available: pages.stern.nyu.edu/~rwiner/CRM%20paper.doc
    • Ying Gao, L. L. (2006). Discussion on Customer Knowledge Management of modern manufacturing environment.
    • Youseff, L., Butrico, M., Da Silva, D. (2008). Toward a Unified Ontology of Cloud Computing. Proc. Grid Computing Environments Workshop, Available: http://www.cs.ucsb.edu/~lyouseff/CCOntology/CloudOntology.pdf [01 September 2010]
    • Wang, W. Tao, T. Kunze, M., Castellanos, Alvaro C. Kramer, D. Karl, W. (2008) Scientific Cloud Cornputing: Early Definition and Experience. High Performance Computing and Cornrnunications, HPCC. 10th IEEE International Conference.
    • Zablah, A. Bellenger, D., Johnston, W. (2004). An evaluation of divergent perspectives on customer relationship management: Towards a common understanding of an emerging phenomenon. Industrial Marketing Management, North-Holland.
    • Zeleny, M. (2005). Human Systems Management: Integrating Knowledge, Management and Systems. World Scientific. pp. 15–16 and 21. Available: http://www.google.com/books?id=Tbb3O5uigCAC&lpg=PR5&ots=tS9bUWAsho&dq=%E2%80%98Human%20Systems%20Management%3A%20Integrating%20Knowledge%2C%20Management%20and%20Systems%E2%80%99&lr&hl=pt-PT&pg=PA23#v=onepage&q&f=false [15 August 2010]
    • Zins, C. (2007). Conceptual Approaches for Defining Data, Information, and Knowledge. Journal of the American Society for Information Science and Technology. Available: http://www.success.co.il/is/zins_definitions_dik.pdf [15 August 2010]