Effect of IT outsourcing on business IT alignment in manufacturing companies

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Master thesis Marcus M. Veen

(student nr. 10645144)

June 2015

Faculty of Science

Information Studies

track Business Information Systems

Prof. Dr. Tom van Engers

Effect of IT outsourcing on

business IT alignment

in manufacturing companies

Supervisors:

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Business IT alignment is everyone rowing in the same direction

Indian snakeboat

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Abstract

Companies in the western world who outsource their IT to lower wage countries are becoming the norm, and this can have an effect on the performance of the IT department and business results. This thesis researches this effect in manufacturing companies, the origin of modern industry. Eight international manufacturing companies are analysed by measuring and comparing IT outsourcing characteristics and the business IT alignment maturity, the persistent number one concern of chief information officers. In this context business IT alignment is defined as everyone rowing in the same direction, which is a complex challenge in our changing world. This requires a common direction and mutual goal which is not self evident in a networked organization spread across the globe with different cultures and languages. IT outsourcing is a dynamic process and can be viewed as a lifecycle with various phases, and occasionally companies back-source their IT after failure.

Based on the eight cases and supported by literature this research indicated that the average business IT alignment of manufacturing companies decreases as a result of IT outsourcing during the transition of personnel, hardware and software. Once the service provider has taken over the IT related activities and a new equilibrium has been accomplished in the new networked organization, the business IT alignment starts to increase again, but slowly. Further the research indicated that it is very challenging to regain the original business IT alignment maturity level after IT outsourcing, and most manufacturing companies will not succeed, which has a negative effect on business performance. To conceptualize this effect a longitudinal model is introduced explaining the business IT alignment alteration in the course of the sourcing lifecycle.

Recuperation of this effect requires an organization with a professional client-customer relationship, and the research indicated that informal communication structures supported by benevolent relationships are crucial. The interpersonal relationships showed to be the dominant factor to align this new networked IT organization with the business and improve company performance. As human beings are the common denominator of all organizations, the negative effect of IT outsourcing on business IT alignment indicated a similar effect for other main industries based on literature.

Keywords

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1 Introduction

Working as a business analyst in the IT department of Tata Steel Europe, an international manufacturing company, my role is to balance the business process requirements and possible IT solutions. This balancing encompasses the interface between the business and IT departments. In literature this is known as business IT alignment (BIA), a complex process and extensively researched subject within information science. Tata Steel Europe already outsourced "captive" their application development and support partially to an affiliated company, and is preparing to increase the outsourcing volume significantly. Tata’s main aim is a more flexible organization, need for technological innovation due to ageing of personnel and cost reduction. The IT department consists of approximately 650 internal employees responsible for all company IT including infra, hardware, software and services. The business operations are performed in 25 larger and smaller plants mainly in the United Kingdom and the Netherlands with more than 35.000 employees in total.

In this context my interest in the effect of IT outsourcing (ITO) on the BIA is both professionally as well as an academic student. According to Chan et al (2007) those organizations that successfully align their business strategy with their IT strategy will outperform those that do not. BIA has also been shown to be a crucial predictor of superior business process performance, IT success, and competitive advantage (Schlosser, 2010). However, practice has demonstrated that successful ITO is not self evident (Delen, 2009) as companies regularly back-source after failure.

During the thesis design phase a literature review was performed to investigate the mechanism how ITO affects BIA. It appeared that the combination of these two subjects is a relevant however not extensively researched topic. As BIA is such a thoroughly studied and complex topic it is surprising how little this is related to ITO considering outsourcing is becoming the norm. One of the first studies in this area was performed by Pollalis (2003) in the banking industry who concluded that ITO could affect business performance positive if IT is well aligned to the business requirements. This suggests that organizations which have a low level of BIA maturity, this will remain the same as a result of ITO. However, properly aligned organizations actually do benefit positively from ITO. Schlosser (2010) studied how companies’ internal alignment and governance processes impact the service quality received from an external ITO provider. Using data from a 154 firms he concluded that good BIA leads to a better and more accurate provider service control process improving service level agreements. Considering IT governance, Schlosser (2010) concluded that the level of the client’s importance to the IT provider positively affects the implementation of governance processes in terms of control mechanisms. This study was performed in the German banking industry. A more recent case study of Silvius (2013) compared four companies to observe the relationship between BIA and ITO. The results showed that two of the cases achieved a higher level of ITO relationship in comparison than the other two cases. The overall conclusion of Silvius (2013) is that there are indications that ITO influences BIA and that this effect is generally positive. However, the ITO model used by Gottschalk and Solli-Sæther (2006) appeared too simple to present the ITO relationship properly.

A more extensive study is performed by Derksen (2013) who researched in a PhD dissertation the impact of ITO on BIA. Derksen analysed cases in Dutch organizations and tested the following hypothesis: “IT outsourcing has a negative impact on business & IT alignment”. The hypothesis was rejected, and the main conclusion was that “ITO does not negatively impact BIA maturity”. Further was concluded that “ITO can have a small positive influence on BIA maturity, based upon the correlation between degree of ITO and BIA”. This is however different in several situations from the contingency perspective (for example industry and size of organization). Overall, the impact is small, although statistically significant. Based upon the research results, “ITO is not in favour but also not negative for BIA maturity”. To refine the dissertation of Derksen his research model is used to investigate the effect of ITO on BIA specifically for manufacturing companies, as differentiation on type of industry was suggested as further research. For this purpose eight international manufacturing companies are investigated using a quantitative method supported with a qualitative verification to measure the effect of ITO on BIA. This revealed a more dynamic perspective how BIA is influenced over time.

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2 Theoretical background

In this chapter a literature review of both IT outsourcing and business IT alignment is elaborated as theoretical background. In addition, the possible influencing factors which could possibly influence the effect of IT outsourcing on business IT alignment are explored.

2.1 IT outsourcing

The main drivers for companies to outsource their IT are generally cost savings (Lacity et al, 2009), strategic and lack of knowledge (Schimmel, 2010). Application development, IT infrastructure and helpdesk are the most commonly outsourced services (Miozzo and Grimshaw, 2005). According to Gwebu et al (2010) it is not self evident that the expected economic value from IT outsourcing (ITO) are delivered at firm level, as the impact on efficiency of operating activities and value chain are mixed. Therefore Gwebu et al (2010) highlight the importance of considering various types of ITO and selecting the appropriate evaluation performance metrics to measure the efficiency improvements. Also IT costs are often not transparent, Gartner (2003) concluded in a benchmark that IT costs are on average 30% more than expected due to hidden costs outside the IT department which will be excluded from the sourcing contract as a result.

According to a recent Gartner study (2014A) organizations that outsource their IT are increasingly focusing on productivity and quality, and not just on labour cost reductions. This is the result of the second or third sourcing cycle, where lessons learned are taken into account. As outsourcing maturity is growing and the complexity of IT is increasing, multiple service partners are often included, referred to as multi sourcing. This also requires a stronger focus on risk and security management especially in a cloud context being less in direct control of assets and activities. In figure 1 the percentage is represented of ITO spend of the total IT spend per industry globally. For manufacturing this is 25%, and it is expected that these figures will only grow in Europe, United States and Asia in the next years.

Figure 1: IT Outsource percentage of IT spend (Gartner, 2014A)

2.1.1 Sourcing lifecycle

The Dutch IT outsourcing expert Delen (2009) has defined ITO as "the transfer of service, where if applicable, the accompanying employees and resources who are transferred to specialised service provider and consequently the rendering back of those processes by that provider as services for the duration of the contract at an agreed-upon level of quality and a financial compensation structure".

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Delen had a leading role in the Dutch platform for outsourcing (PON1) which introduced a sourcing lifecycle (PON, 2006) describing the five phases as reflected in figure 2 below.

Figure 2: The PON sourcing lifecycle (PON, 2006)

A short description of these five phases is included in table 1 below based on Delen (2009).

# Phase Description 1 Decision

taking

Company considers potential IT outsourcing with as most common factor the reduction of costs and improvement of quality.

2 Provider selection

The customer makes a selection of IT service providers based on facts and commercial insights, commonly using the information service procurement library (ISPL).

3 Transition Three sub phases can be distinguished:

-Unbundling: separation of personnel, hardware and software

-Transferring: transfer of services to service provider (including accompanying resources) -Transforming: transformation of services and adjustment of resources in service providers environment and capabilities.

4 Services Ongoing process where both parties manage services from their individual perspectives, also defined as demand and service management.

5 Contract termination

The sourcing contract is terminated after a pre determined period has expired, or prematurely in case of discontent.

Table 1: Five phases of PON sourcing lifecycle (Delen, 2009)

To support the success of the sourcing lifecycle Delen (2005 and 2012) has defined nine controllable success determinants which are listed below:

1. Working according to the transition plan; outsourcer as well as service provider, 2. Managing the business case for outsourcing,

3. The service supplier should manage his own business case, 4. Staff transfer of outsourcer,

5. Assets transfer of outsourcer; hardware, software and accompanying knowledge, 6. Demand management; ability to manage the service provider,

7. Retention of expertise; to support back-sourcing or changing from service provider, 8. Communication inside the outsourcer’s organization with all stakeholders,

9. Communication inside the vendor’s organization with all stakeholders.

1

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After the sourcing lifecycle is completed, the outsourcing company has the following three options:

• Extend the contract and continue with the service provider,

• Transfer the sourcing contract to a new service provider,

• Back source the IT services from the service provider.

2.1.2 Cultural differences

Collaboration and communication between the outsourcer and service supplier will be affected by cultural differences during the outsourcing lifecycle. According to Gartner (2014) India will remain the largest supplier despite emerging capacity in other regions such as Eastern Europe. Hofstede (2002) has introduced five dimensions to measure the cultural differences being:

• Power distance index,

• Individualism versus collectivism,

• Masculinity versus femininity,

• Uncertainty avoidance index,

• Long term orientation versus short term normative orientation.

Considering these dimensions and anticipating on them through the sourcing lifecycle, they could attribute to sustain the relationship and improve mutual understanding. These dynamics have been studied by Jebli (2014) who concluded that cultural differences are a major challenge in an offshore context. Intercultural differences in offshore virtual teams are not only expressed through electronic communication but also through the way of perception and execution of daily work tasks. Jebli (2014) emphasizes the importance of observational learning which can support a better understanding of other cultures in the team and a sense of control regulation for commitment and agreement. He also highlighted the importance of work satisfaction and recognition by creating autonomous rules to adjust control regulation.

2.1.3 IT outsourcing maturity

To measure ITO considering both parties involved in the contract, Gottschalk and Solli-Sæther (2006) have introduced a maturity model describing three stages as reflected in figure 3 below.

Figure 3: Maturity model for ITO Gottschalk and Solli-Sæther (2006)

In the ITO maturity model of Gottschalk and Solli-Sæther (2006) the three stages of growth are sequential and occur as a hierarchical and not easily reversed progression involving a broad range of activities and structures.

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Also eleven benchmark variables are suggested which are applicable per individual stage; these are listed below in table 2.

# Variable 1. Cost 2. Resource 3. Partnership

1 Economic benefit Cost minimization and operational efficiency

Business productivity, technology innovation

Business benefits, mutual goals

2 Primary transactions Infrastructure Applications Joint investments 3 Contractual

completeness

Specified obligations Key competence, critical projects, access to resources

Profit sharing, personnel exchanges

4 Vendor behaviour control Service level agreements Project performance service quality

Strategy implementation 5 Demarcation of labour Procurement Innovation projects Continuous innovation 6 Core competence

management

Client defines technology requirements Vendor is regarded as a strategic resource Co-developing business processes 7 Vendor resource exploitation

Excellent operations Technology initiatives Complementary, capabilities, skills, competences & methods 8 Alliance exploitation Account manager; IT

manager

Operations & business manager

Business manager 9 Relationship exploitation Inter firm information

sharing

Joint planning Relational norms 10 Social exchange

exploitation

Low Medium High

11 Stakeholder management Economic interests has priority

Recognizing a number of stakeholder groups

Balancing interests

Table 2: ITO bench mark variables Gottschalk and Solli-Sæther (2006)

According to Gottschalk and Solli-Sæther (2006) the critical ITO success factor to manage an outsourcing relationship is "to exploit the opportunities and avoid the threats for which a mutual understanding of their relationship stage is a prerequisite". If both parties agree to move to the next step they can join their resources to identify and realise the benefits.

2.1.4 Outsourcing failure

Barthémely (2003) has introduced seven deadly sins underlying most failed outsourcing efforts based on a survey of nearly one hundred cases in Europe and the United States. These seven sins are sequentially ordered, dividing the outsourcing into three stages. These are the original idea, beginning of relationship and changing vendor. Barthémely (2003) has provided also the lessons learned for each individual deadly sin which are reflected in table 3 below.

# Deadly sin Lesson learned Time table

1 Outsourcing activities that should not be outsourced

Only activities that do not belong to the core business can be safely outsourced. The core vs. non-core approach can be implemented both at the firm and activity level.

2 Selecting the wrong vendor

Outsourcing clients should look for vendors that are able to provide state-of-the-art solutions and are trustworthy

3 Writing a poor contract

The contract is the main tool to establish a balance of power in outsourcing relationships. Good contracts have four characteristics. They must be precise, complete, balanced, and flexible

Original idea to outsource

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4 Overlooking personnel issues

Loss of key employees and lack of commitment can seriously threaten the viability of outsourcing efforts. However, good communication and ethical behaviour towards employees can help avoid such problems

5 Losing control over the outsourced activity

In order to keep control over outsourced activities, clients must retain a small group of qualified managers. An active management of the vendor is also crucial.

6 Overlooking the hidden costs of outsourcing

The hidden costs (i.e., search, contracting, and managing costs) can threaten the viability of outsourcing efforts. Hidden costs are likely to be lower when commodities are outsourced.

Beginning of the relationship

7 Failing to plan an exit strategy

The end of the outsourcing contract must be planned from the outset. Building reversibility clauses into the contract is crucial.

Vendor switch or reintegration of the outsourced activity Table 3: Seven deadly sins of outsourcing and lessons learned, Barthémely (2003)

Barthémely (2003) emphasises that some sins are "deadlier" than others. The mistakes "outsourcing activities that should not be outsourced", "writing a poor contract," and "failing to plan an exit strategy" have appeared to be the most frequent. The main message of Barthémely is that some outsourcing efforts are already doomed to fail even before the actual relationship with the vendor started. And to be successful companies need to accumulate the required outsourcing expertise to avoid these seven deadly sins.

In additionally the hidden costs of outsourcing are often not indentified and Barthémely (2001) introduced following four categories:

• Vendor search and contracting,

• Transitioning to the vendor,

• Managing the outsourcing effort,

• Transitioning after outsourcing.

As cost savings are one of the main reasons for IT outsourcing (Lacity et al, 2009) these hidden costs should not be underestimated (Barthémely, 2001) and efforts should be made to reduce and include these to calculate a more realistic business case.

Summary IT outsourcing

Most common IT outsourcing projects are initiated to realise cost saving targets (Lacity et al, 2009) starting with application development, IT infrastructure and helpdesk (Miozzo and Grimshaw, 2005). In some industries the total outsourced IT spend is already exceeding 30% (Gartner, 2014A) and these figures are expected to grow in future. IT outsourcing introduces a lifecycle Delen (2009) with five different phases and a number of success determinants. Once the cycle is complete typically the contract is extended or transferred to a new service provider, or alternatively back sourced. The level of ITO can be measured, for example using the model of Solli-Sæther (2006) and is influenced by cultural differences as the sourcing partners are often off shore parties driven by lower wages. There are many described cases were sourcing failed and Barthémely (2003) has described seven deadly sins explaining the underlying most failed outsourcing efforts, and mentioned the hidden costs.

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2.2 Business IT alignment

Henderson and Venkatraman (1993) have introduced the strategic alignment model (SAM) with the main message that IT strategy should be aligned with business strategy to become a successful company. This model (see figure 4 below) defines four fundamental domains of strategic choice to leverage information technology for transforming organizations being:

• Business strategic choice,

• Information technology strategy,

• Organizational structure and processes,

• Information technology infra structure and processes.

Figure 4: Strategic Alignment Model, Henderson and Venkatraman (1993)

The strategic alignment model has been the basis for many successful pieces of research aiming to realise a maximum value from IT investment (Maes et al, 2000). This mechanism is commonly defined in information science as business IT alignment (BIA).

2.2.1 Business IT alignment definitions

Two decades after the strategic alignment model (Henderson and Venkatraman, 1993) was introduced BIA is still a very much a live topic within information management, supported with many studies. In table 4 below a number of BIA definitions are listed in chronological order as reference.

Business IT alignment definition Author

The mapping between IS strategy and business strategy so that IT is deployed for supporting competitive advantage

Baets (1992) The allocation of IT budgets such that business functions are supported in an

optimal way.

Henderson and Venkatraman (1993) The degree of congruence of an organization's IT strategy and IT infrastructure

with the organization's strategic business objectives and infrastructure.

Broadbent and Weill (1993) The degree to which the IT mission, objectives, and plans support and are

supported by the business mission, objectives and plans.

Reich and Benbasat (1996) The situation that occurs when IS functions are amalgamated with the most

fundamental strategies and core competencies of the organization

Chan et al (1997) A continuous process, involving management and design sub processes, of

consciously and coherently interrelating all components of the business/IT relationship to contribute to the organization's performance over the time.

Maes et al (2000)

The process of achieving competitive advantage through developing and sustaining a symbiotic real relation between business and IT.

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A state where IT is applied in an appropriate and timely way, in harmony with business strategies, goals and the needs.

Luftman (2003) Managing the resources such as people, technology, and outside resources to

provide a set of IT services and capabilities that are in line with the needs and priorities of the businesses.

Moody (2003)

Ensuring that every single action performed by IT individuals is focused on building and delivering shareholder/ stakeholder value by supporting business operations and/or achieving business goals.

Senn (2004)

Alignment is the business and IT working together to reach a common goal. Campbell (2005) Strategic alignment is everyone rowing in the same direction. Abraham (2006) The process to make the services offered by IT support the requirements of the

business - whether such services are offered individually by one participant in the collaborative networked organizations (CNO) or collaboratively by the entire network - so that value is created for the participating organizations of the CNO.

Santana Tapia (2009)

Table 4: BIA definitions

There is also criticism on BIA, for example Ciborra (1997) questioned the commercial motives of Henderson and Venkatraman and referred to the scientific paradigm of the hard sciences. Also Chan et al (2007) were critical and argued that corporate strategy is often unknown, unclear or difficult to adapt, and therefore alignment with IT strategy is hard. However, according to a recent international study of Derksen and Luftman (2014) the “perennial number 1 concern of information managers in Europe but also world wide is still business IT alignment”.

2.2.2 Business IT alignment maturity

Being such an important topic various models have been introduced to measure the BIA maturity to make it tangible and comparable. The model of Luftman (2000) is broadly accepted and used widely for the purpose to measure the BIA maturity, and in this context it is quoted in hundreds of scientific information science articles. The BIA measurement model of Luftman uses six different business IT alignment maturity criteria. These are communications, value measurement, governance, partnership, scope & architecture and skills & competences. Each individual criterion can be measured using a number of characteristics, and is assessed on five maturity levels as reflected in figure 5 below.

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The five maturity levels of business IT alignment as proposed by Luftman are: 1. Initial/ad hoc process,

2. Committed process,

3. Established focused process, 4. Improved/managed process, 5. Optimized process.

In figure 5 the differences of these maturity levels are explained per individual criterion.

According to Luftman (2000) most organizations are at level two of this maturity scale, and this alignment maturity assessment provides a vehicle to evaluate where an organization is and where it needs to go to attain and sustain BIA. In a succeeding research using the same maturity scale seven years later Luftman and Kempaiah (2007) conclude that most organizations are at a remarkably consistent level of three suggesting improvement, however BIA is still a persistent issue according to Derksen and Luftman (2014).

2.2.3 Interventions to improve business IT alignment

Poels (2006) wrote a PhD dissertation to investigate which interventions lead to a better alignment between business and information technology studying several cases in leading financial service providers. Poels (2006) defines BIA as "the best possible use of IT resources to meet enterprise objectives". He selected 12 interventions which improve the BIA and arranged these into three different categories which are briefly described below.

• Interventions that lead to a better dialogue as there are many formal and informal relationships the

business and IT service provider. Dialogue should connect the strategy of the firm to relationships between IT projects, and a chief information officer (CIO) could translate business goals to into IT opportunities especially in a multidisciplinary environment. Also increasing the improvement of power on the business demand side appeared successful.

• Interventions that improve business economics, for example by making IT costs of employees and

other resources transparent. In addition, organising IT portfolio management and IT investment procedures based on a business case improve the BIA.

• Interventions that strengthen the IT core competencies, for example position in IT architecture properly is important. Additionally by awarding multidisciplinary team performance, stimulate and initialising experiments and establish IT wards will support the maturity of BIA. Also re-organising IT core competencies and outsourcing the remaining could contribute.

Comparing these interventions with the criteria of Luftman (2000) the methodologies overlap, however in the opinion of Poels (2006) these interventions are the most critical influencing BIA. In general Poels found out that the size of the organization did not influence BIA, and eagerness to learn and act on outcome did have a positive affect on the extend of BIA.

Summary business IT alignment

BIA was introduced by Henderson and Venkatraman (1993), and is still a persistent issue (Derksen and Luftman, 2014). To measure BIA maturity measurement the model of Luftman (2000) is a commonly used and accepted model using six criteria being communication, competency/value measurement, governance, skills, scope/architecture, and partnership measured on 5 levels. Poels (2006) introduces three interventions which can improve BIA focussing on the dialogue, business economics and strengthening the IT core competencies, and concluded that the size of the organization did not influence BIA.

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2.3 Possible influencing factors

This chapter explores the possible influencing factors considering the effect of IT outsourcing on business IT alignment. Some factors can be more important than others, but this is not further distinguished or analysed.

2.3.1 Chief information officer

Focussing on the partnership criteria, Luftman and Kempaiah (2007) emphasise that this can be strengthened between the business and IT by introducing a chief information officer (CIO) on the level of chief executive officer (CEO) who both share a clearly defined vision. Also governance is important especially in large manufacturing companies as IT operates commonly as a cost centre (Luftman and Kempaiah, 2007). Prioritising of IT projects is reactive to business needs and a CIO could improve this mechanism. The importance of the CIO role in relationship to BIA is also supported by the research of Weil and Woodham (2002), Chan (2002) and Balocco (2013), especially in the area of governance. 2.3.2 Informal organization structures

According to a study of Chan (2002) better BIA improves the performance of information system functions. However, Chan is critical considering the formal organization structures. She found in her research among eight cases supported by literature that the informal organization structures do play a far more important role than expected in improving the performance of information systems. This informal effect appears “more during compared to the formal structure which is more transient” (Chan, 2002). Therefore attempts to improve overall BIA and information systems performance, management effort should be spent on improving the robustness of the informal organization, defined as "the relationship based structures that transcend the formal division of labour and coordination of tasks", instead of aligning formal structures.

2.3.3 Business IT alignment in collaborative networked organizations

Santana Tapia (2009) has investigated various BIA maturity models to support his research considering BIA in collaborative networked organizations (CNO). Outsourcing introduces by definition a collaboration of at least two organizations and this is considered to be a networked organization. Therefore this research is relevant in the context of this thesis and is explored in more detail. Santana Tapia (2009) defines a CNO as “any mix-and-match network of profit-and-loss responsible organizational units, or of independent organizations, connected by IT, that work together to jointly accomplish tasks, reach common goals and serve customers over a period of time”.

From his research Santana Tapia (2009) concluded that there are four main domains which can be used to measure the BIA maturity in a CNO to benchmark and support continuous improvement of BIA process. Each domain being partnering structure, IS architecture, process architecture and coordination has five levels of maturity with specific characteristics, this is represented in figure 6 below.

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Comparing the measurement model of Santana Tapia (2009) with the model of Luftman (2000) there are overlapping areas and similarities, however with divergent terminology usage and detail. On high level the partnering structure domain compares to the partnership and communication criteria, IS architecture domain compares to the competency/value measurements and scope/architecture criteria, and coordination domain compares to the governance and skills criteria. Looking at the noticeable differences the domain of process architecture is introduced supplementary by Santana Tapia (2009) compared to Luftman (2000). Considering the model of Santana Tapia (2009) is aiming at a networked organization, the process architecture domain is the distinguishing factor to measuring the inter-organizational process as well. As this domain is more business oriented representing business process descriptions and performance measuring business process modelling (BPM) could support this aspect positively.

2.3.4 Universal principles

Making IT work has little to do with technology itself according to Feld and Stoddard (2004). They state that there are three interdependent, interrelated, and universally applicable principles for executing IT effectively being:

• Long-term IT renewal plan linked to corporate strategy overarching a multiyear period,

• Simplified, unifying corporate technology platform; which is typical for an ERP system,

• Highly functional, performance oriented IT organization working according to corporate standards.

Feld and Stoddard (2004) state that once these three principles are aligned and locked together, IT organizations and supporting systems tend to deliver expected results rapidly within six months.

2.3.5 Changing environment

Organizations change constantly to remain viable and competitive. This mechanism is described by Abcouwer and Parson (2011) as the adaptive cycle of resilience. In this model (see figure 7 below) all changes start with a crisis, e.g. the sales of the flagship product are collapsing, after which the organization starts looking for new combinations to keep in business. Once a new market or product has been targeted a new entrepreneurial phase starts ending in a new equilibrium if the changed organizational targets have been met again.

Figure 7: Adaptive cycle of resilience, Abcouwer and Parson (2011)

This cycle is influenced by a constantly changing environment with unpredictable factors having a drastic effect on the business and IT requirements thereby affecting the BIA. These changes could be amplified in case of IT outsourcing considering this network as a viable system model (Beer, 1984) making it more complex. Therefore the exploiting or exploring state of an organization could potentially affect the relationship between BIA and ITO as a result of this mechanism.

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2.3.6 ERP in manufacturing companies

Enterprise resource planning (ERP) systems are commercial software packages integrating the information flowing through a company (Maas, 2014). This software supports all main business processes such as manufacturing, inventory management, sales, shipping, human resource and finance making it essential for medium and large size companies. Estimates have been made indicating that approximately 75% of medium to large manufacturing companies have implemented ERP (Morris and Venkatesh, 2010) and even 80% among Fortune 500 firms. Implementation of ERP systems introduces fundamental changes to the nature of tasks, workflows, and the jobs themselves due to the embedded predefined functional structure and organizational choices affecting BIA (Millet, 2013). Considering the ERP system as an important technological artefact in the organization, it should be viewed as a key driver of job design and organizational change strategies as well (Morris and Venkatesh, 2010). However, when the users of ERP do not use it to its full extent the expected benefits are unlikely to be obtained and subsequent increases in performance will not occur (Murphy and Chang, 2012). According to Gartner (2014B) a CIO survey highlighted that ERP is the core application, with SAP as market leader, and enterprise business applications in general are responsible for almost half of the IT investments to improve business. The Gartner survey also revealed that a gap is developing between the business users of enterprise applications such as ERP and the IT professionals charged with supporting these applications. This leads to strategic misalignment slowing down IT deployment to solve specific problems or respond to new market opportunities.

According to Soffer (2005) one of the main problems in ERP projects is to align an off the shelf software package with the business processes as the system is designed to serve a large variety of enterprises by default. Despite the common wisdom suggesting that enterprises should standardise their business processes and align with best practice, this it is not always the case (Koch, 2001). Koch states that ideally “business process reengineering and ERP are complementary”, this is however a continuous challenge considering the integrated nature connecting all requirements and possible solutions.

As with all IT systems ERP applications can be outsourced and is considered to be a commodity according to Gartner (2014A). Olson (2007) evaluated the outsourcing of ERP and emphasises that costs can rise precipitously after the outsourcing firm has become committed to the relationship introducing a number of important issues. Therefore multiple criteria analysis should be incorporated to minimise quantified factors into rational decision models which is described by Kahraman (2010). 2.3.7 Governance model

IT governance is a critical success factor to align and optimise the various business processes (Luftman and Kempaiah, 2007). Therefore information management should be organised effectively, and the integrative generic framework for information management of Maes (2000) suggests how this can be structured, see figure 8 below.

Figure 8: Generic framework IS, Maes (2000)

From this perspective it appears that governance is required at various levels to connect and align the nine planes in the organization, ideally at individual, team and departmental level.

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A similar alignment mechanism has been further researched by Fonstad (2006) who has introduced an IT engagement model for this purpose with following two fundamental goals:

• Alignment between IT and the rest of the business and,

• Coordination across multiple organizational levels.

According to Fonstad (2006) a key success factor to IT governance is the linking mechanisms bringing together key stakeholders such as informal communication to ensure that IT projects achieve both local and company-wide objectives. To enable ideas flowing back and forth between company-wide IT governance and project management, linking mechanisms are the heart of a company’s IT engagement model. This ensures that high-level governance decisions are understood and implemented by project teams (Fonstad, 2006), enabling projects to achieve the company’s objectives and lessons learned from each project. Notable the linking appeared “affective in both informal as well as informal meetings suggesting this can not always be orchestrated” (Fonstad, 2006).

2.3.8 Case study

A recent case study of Silvius (2013) compared four companies to observe the relationship between BIA and ITO. To measure BIA the strategic alignment maturity model of Luftman (2000) was used, and to measure ITO the maturity model for ITO of Gottschalk and Solli-Sæther (2006). The assessments followed the process as suggested by Ekstedt et al (2005) performing the semi structured interviews with the lower levels in the organization as well. The results showed that two of the cases achieved a higher level of ITO relationship in comparison than the other two cases. In all four cases the scores on governance maturity and scope & architecture maturity were remarkably high and the scores on skills maturity remarkably low. This finding is contradicting to Luftman and Kempaiah (2007) who suggest that all the six variables should be developed in a more or less equally manner. This could indicate that ITO has actually a positive effect on the BIA maturity of governance and scope & architecture maturity. The lower score on skills is also surprising as Thorogood et al (2004) have identified that improved skills are one of the aspects of alignment on which ITO actually could help.

The overall conclusion of Silvius (2013) is that there are indications that ITO influences BIA and that this effect is generally positive. Silvius suggests a number of factors which could influence the relationship between ITO and BIA and would require further research, as included in table 5 below.

# Influencing factors

1 Difference in assessment level of the ITO relationship

2 Proactive attitude and behaviour of the service provider

3 Involvement of IT end-users in the ITO relationship

4 Innovation requires partnership

5 Service providers that employ former employees of the outsourcers

6 The monetary value of the ITO contract

7 Corporate restructures deteriorate ITO relationships

Table 5: Possible factors influencing relationship ITO and BIA, Silvius (2013)

Summary influencing factors

A chief information officer is a strong enabler to improve the BIA criteria (Luftman and Kempaiah, 2007). To improve BIA the informal organizational structure was indicated to be of relevant importance and needs to be stimulated consciously for this reason (Chan, 2002). Also business process architecture should be considered to measure BIA according to Santana Tapia (2009), especially in collaborative networked organizations using business process modelling. Considering the changing environment where organizations commonly act (Abcouwer and Parson, 2011), the lifecycle stages of exploiting and exploring can influence the BIA. Despite ERP systems are common in manufacturing companies they are still complex to support considering their integrated nature. Therefore effective governance is required to align and link all involved stakeholders both formal and informal. Also the IT outsourcing relationships was indicated to be strong influencing factor on BIA according to Silvius (2013). A number of these potential influencing factors are suitable to be used in the questionnaires of the multiple case researches.

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3 Methodology

3.1 Problem discussion

Manufacturing companies outsource their IT for approximately 25% on a global scale, and it is expected this percentage will grow in future (Gartner, 2014A). Kahraman et al (2010) state that "the performance of the service provider directly affects the main firm’s performance", especially when an ERP system is involved. Therefore selection of the most appropriate service provider is an extremely important decision affecting the business IT alignment (BIA) potentially negative. Derksen (2013) suggested further research considering the BIA alignment maturity among different industries that outsource their IT. In the context that an internal IT department of an (international) manufacturing company is outsourced, my interest focuses on the effect on BIA. The effect of IT outsourcing could potentially jeopardize the manufacturing company’s results, and understanding this mechanism is therefore scientifically relevant. To research this problem following hypothesis is proposed:

IT outsourcing has a negative effect on business IT alignment in manufacturing companies.

3.2 Approach

The research approach is based on a multi-strategy design combining quantitative as well as qualitative data collection methods, and according to Robson (2011) there is greater variety of the potential benefits when these two paradigms are brought together. Also Bryman (2006) mentions that a multi-strategy (or mixed-methods) design will produce a more comprehensive and complete picture of the research topic. To justify the combination of both quantitative and qualitative data collection methods, Bryman (2006) states following five potential benefits:

• Triangulation as corroboration between the data will enhance the validity of the findings,

• Complementarities to seek elaboration, enhancement and clarification producing a more

comprehensive and complete picture,

• Development to use the results from one method to develop the other,

• Initiation seeks the discovery of contradiction and paradox to recast questions or results from one

method to the other,

• Expansion to extend the range of enquiry and breadth using different methods.

The research uses a quantitative method to measure the business IT alignment maturity level and IT outsourcing characteristics at a number of manufacturing companies. For this purpose a structured questionnaire is used. The collected quantitative results are subsequently analysed and compared to industry statistics. The interim results are verified using a semi structured interview with the interviewees. By coding the interview notes the qualitative verification is finalised. By combining the results of both data collection methods, the findings are discussed and final conclusions are drawn.

3.3 Research question

To test the proposed hypothesis following research question is formulated:

To what extent effects IT outsourcing the business IT alignment inmanufacturing companies?

To answer this research question the following sub questions should be answered: 1. Which factors influence business IT alignment of manufacturing companies?

2. Multiple case studies: what business IT alignment and IT outsourcing maturities are measured for manufacturing companies applying the research model of Derksen (2013)?

3. What are the similarities and deviations of the case studies compared to the results of Derksen (2013) and Luftman (2000) specifically for manufacturing companies?

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3.4 Research design

To answer the sub questions as described above following research methods are distinguished.

• Extensive literature research explaining business IT alignment, IT outsourcing and possible

influencing factors to answer sub question 1.

• Applying the Derksen (2013) research model using quantitative questionnaires at a number of case

studies at manufacturing companies to answer sub question 2. The quantitative results are qualitative validated using semi structured interviews for all cases.

• Determine similarities and deviations with a quantitative statistical analysis based on the case data

of sub question 2 and the results of Derksen and Luftman to answer sub question 3, supported with the qualitative verification results.

• Based on the quantitative and qualitative data analysis supported by the literature research the similarities and deviations will be examined and explained to answer sub question 4, and generalised.

These steps are reflected in figure 9 below.

Figure 9: Research design for research questions

3.5 Case selection

The cases are selected through a network of the Dutch association of SAP users (VNSG2) who all use

the same ERP system and exchange experiences and share knowledge. Being a member of the enterprise asset management (EAM) focus group, all manufacturing companies were selected from the members list and asked for their collaboration. The VNSG EAM focus group has approximately 250 members from a variety of different companies. Especially the manufacturing companies are commonly active internationally with branches outside the Netherlands as well. Based on Mintzberg (2007) these manufacturing companies can be classified as a machine bureaucracy as they depend primarily on the standardization of operating work processes for coordination.

This approach will make the sample set compatible as all manufacturing companies have a similar type of ERP system and the interviewees have a common frame of reference.

2

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4 Conceptual framework

In this chapter the research model of Derksen (2013) is described in more detail as it will be used as conceptual framework of this thesis. The case studies of the manufacturing companies will measure both the IT outsourcing (ITO) characteristics and the business IT alignment (BIA) maturities to compare. Therefore first a generic description is given of the Derksen research model. In addition the research measurements are explained of the ITO and BIA maturity, and his results to explain the details and context. By applying the Derksen research model to manufacturing companies the effect of ITO on BIA can potentially be refined in more detail within this specific domain.

4.1 Derksen research model

The research model of Derksen (2013) describes how ITO influences BIA and is reflected in figure 10 below including contingency factors affecting possibly this mechanism.

Figure 10: Contingency factors ITO influencing BIA Derksen (2013)

Derksen (2013) uses following definitions:

• ITO is “a process whereby an organization decides to contract out or to sell the firm’s IT assets, people and/or activities to a third party supplier, who in exchange provides and possibly manages these assets, people and/or activities for a fee over an agreed period of time”.

• BIA is “realising and optimizing in an on-going process; the relational mechanism between business

& IT by working on the IT effectiveness of the organization in order to realise enterprise business objectives”.

The PhD dissertation of Derksen (2013) tested the following hypothesis: “IT outsourcing has a negative impact on business IT alignment”. Additionally following industry questions are answered:

• Does BIA differ depending on the degree of ITO?

• On which aspects / areas of interest does the BIA differ?

• Does ITO influence the level of BIA maturity?

• What are the determining characteristics for BIA in ITO situations?

The hypothesis was rejected, and the main conclusion was that “IT outsourcing does not negatively impact BIA maturity”. Further was concluded that “ITO can have a small positive influence on BIA maturity”, based upon the correlation between "degree of ITO" and "BIA maturity". This is different in several situations from the contingency perspective (for example industry and size of organization). Overall the impact is small although statistically significant. Based upon the research results, “ITO is not in favour but also not negative for BIA maturity”.

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4.2 Research measurements

To measure BIA Derksen (2013) uses the strategic alignment maturity model of Luftman (2000) as described in chapter 2.2.2 previously (and questionnaire in appendix 2A). To measure ITO Derksen (2013) has identified following ten characteristics based on various ITO literature to differentiate ITO (Barthémely, 2003; Delen, 2003; Delen, 2005; Gianotten, 2008; Koh et al (2004) and Oosterhaven, 2008). These ITO characteristics are reflected in table 6 below.

# ITO characteristics Measuring the maturity of 1 Type of ITO relationship The partnership

2 Scope op ITO - organizational Organization structure 3 Scope of ITO - functional scope Functional areas 4 ITO vendor construction Vendor construction 5 Governance of ITO Demand governance 6 ITO experience Relationship with supplier 7 ITO contract Contract agreements 8 ITO project management Supplier project management 9 ITO service level management Service level agreements 10 ITO transition result Employee transfer

Table 6: ITO characteristics, Derksen (2013)

Each of these ten characteristics (see questionnaire in appendix 2B) can be measured using five ITO degrees based on Gianotten (2008) which are included in table 7 below.

# Degree Functional scope (contract value related)

Size of ITO deal (contract value IT budget)

1 None <10% <5%

2 Limited 10-25% 5-10%

3 Partly 26-50% 11-25%

4 Significant 51-75% 26-50% 5 Completely >75% >50%

Table 7: Classification degree of ITO, Gianotten (2008)

From these ten ITO characteristics Derksen (2013) has defined the “degree ITO” and “ITO maturity” based on a subset of these characteristics, and compares only the “degree ITO” with BIA to draw his main conclusion. The definition of “degree ITO” and “ITO maturity” is reflected in appendix 5 by colour coding the individual (sub) characteristics used to calculate the maturity level.

4.3 Research results

The contingency factors which could possibly influence the ITO and BIA relationship are split by organizational and people & culture factors.

• The organizational contingency factors are defined as industry, size, geographical area, role of

respondent and business & IT proposition.

• The people & culture contingency factors are defined as attitude, behaviour and culture. The research data of Derksen (2013) was gathered using three different approaches being:

1. Case research including 28 cases used for more detailed analysis, 2. Survey research performed at 183 organizations,

3. Short survey research: 62 organizations mainly for housing corporations and education.

This produced a data set representing a cross section covering various Dutch organizations, industries and sizes. Considering this large data set some findings within the three research approaches showed

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some contradictions. For example, the case research has been performed from both the business and IT perspectives as reflected in figure 11 below, which indicated slightly different results for the 28 case researches.

Business perspective IT perspective

Figure 11: Scatter diagram degree ITO and BIA score (n=28), Derksen (2013)

In addition some results diverged from the main conclusion that IT outsourcing does not negatively impact BIA maturity, especially from the business perspective which suggest actually the opposite. The main conclusion was drawn from a larger data set representing 169 organizations from the survey research, however without breaking this down by individual contingency factors. This is reflected in figure 12 below indicating a positive correlation between the degree ITO and BIA.

Figure 12: Scatter diagram degree ITO and BIA score (n=169), Derksen (2013)

4.4 Research opportunities

Derksen (2013) stated that there are differences in degree ITO and BIA score based upon the following contingency factors: industry, size of organization, role respondent, business proposition, IT proposition and people & culture. Therefore Derksen suggested that the main conclusion can be refined by investigating the suggested contingency factors or additional ones. The dissertation included a number of further research suggestions such as differences and impact of industries on correlation between degree IT outsourcing and BIA maturity.

The research data of Derksen contains many housing corporations, education industries and government organizations in the Netherlands. This could have biased or limited the overall conclusion to be generalised. As a result there is an opportunity to refine the research of Derksen considering manufacturing companies and their more complex multidisciplinary integrated business processes commonly supported by ERP systems (Gartner, 2014B).

Therefore the Derksen (2013) research model is used in this research as conceptual framework to measure the effect of IT outsourcing on business IT alignment in manufacturing companies. In addition the questionnaire is extended with possible influencing factors on this effect (see appendix 2C).

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5 Analysis and results

In this chapter first the eight studied companies are described on a high level, in order to make them anonymous a rowboat type is used. This is suitable considering my definition of business IT alignment (BIA) as “everyone rowing in the same direction”. Subsequently the quantitative results on BIA maturity are analysed based on the six criteria of Luftman (2000), and first this is done extensively for Tata Steel Europe (“Snakeboat”) as main case. Also the BIA results are compared with data from literature for manufacturing companies as well as other industries to verify the trends and statistical relevance. Next the quantitative IT outsourcing (ITO) results are analysed using the ten ITO characteristics of Derksen (2013). All quantitative data is analysed and verified with the qualitative interviews and coded notes (appendix 3 & 7) supported by literature. Finally the correlation of all results is analysed and elucidated.

5.1 High level company description

As introduction a high level company description is given of the eight manufacturing companies which have been researched (see chapter 3.5) in table 8 below.

Nr. Company Product Area Employees [x 1000]

ITO length [years]

ITO budget [% of total] 1 Snakeboat Steel Europe > 10 > 6 26 - 50 2 Canoe Agriculture Global 1 - 5 2,5 - 4 >50 3 Kayak Soft drinks Netherlands 0,25 - 0,50 > 6 26 - 50 4 Skiff Construction Europe 5 - 10 < 1 26 - 50 5 Galley Electronics Global > 10 > 6 26 - 50 6 Sampan Cosmetics Global 1 - 5 1 - 2,5 11 - 25 7 Gondola Aviation Europe > 10 2,5 - 4 11 - 25 8 Longboat Petrochemical Global > 10 > 6 >50

Table 8: Company description eight cases

Table 8 reflects that the studied manufacturing companies are diverse in product, area and employees, have various ITO lengths and budgets providing a sound reflection of this industry.

5.2 Business IT alignment maturity results

5.2.1 Business IT alignment Tata Steel Europe

To apply the maturity model of Luftman (2000) fifteen individual questionnaires have been conducted in both the IT (n=8) and business (n=7) departments of Tata Steel Europe measuring the business IT alignment (see figure 5). All interviewees are senior managers from both the Netherlands and UK which resulted in a balanced overview as reflected in figure 13 below (details included in appendix 3A).

Figure 13: Comparing BIA maturity scores of the IT and business departments of TSE

Criteria IT Bus Delta

Communications 2.79 2.21 0.58 Value measure 2.48 2.14 0.34 Governance 3.25 2.59 0.66 Partnership 3.08 2.36 0.73 Scope and Arch. 2.93 2.51 0.41 Skills and comp. 2.32 2.05 0.27

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From figure 13 it can be seen that the BIA assessment of the business stakeholders is lower than the IT department on all criteria with an average delta of 0.50.

• The maximum delta is for the partnership (0.73) and governance (0.66) criteria, indicating that the

business stakeholders view the IT department not as preferred partner. The interviews indicated this is boosted during governance meetings where the business and IT interests conflict, mainly about delivery responsiveness (“the biggest issue in the IT department is the time to react on new requirements”) and business process alignment (“IT governance has no added value”).

• The minimum delta is for the skills and competences (0.27) and scope and value measurement

(0.34) criteria, meaning that the IT knowledge and performance is perceived by the business as least different. A striking finding is the very low score on skills and competences compared to the other criteria, and the IT department has roughly the same view as was mentioned in the interviews (“business knowledge is draining from the IT department”).

Apparently from the business perspective the business IT alignment is worse than from the IT perspective. Based on the interviews (see appendix 3B) this is mainly the result of a decrease of IT performance caused by IT outsourcing (“previously IT was an enabler for strategically goals but this has decreased”) as well as the difficult financial period with continuous restructuring and savings. As IT is the core activity of the IT department, their perspective is narrowed loosing somewhat sense of business operations and practice, especially since ERP was outsourced (“the IT department is too occupied with internal instead of business processes”). A similar observation was made by Derksen (2013) but this is conflicting with Luftman and Kempaiah (2007) who noted the opposite for companies where IT outsourcing is unknown: “the business executives generally ranked alignment maturity higher than the IT executives”. A possible explanation could be that IT outsourcing has reduced the satisfaction of the business as described by Kim and Chung (2003).

Conclusion 1: In manufacturing companies who outsource their IT the average business IT alignment maturity is scored lower by the business department than the IT department.

In figure 14 the average BIA of Tata Steel Europe is compared with the average of manufacturing peers based on Luftman and Kempaiah (2007) for 46 manufacturing companies.

Figure 14: Comparing Tata Steel Europe average BIA maturity scores (n=15) with peers (n=46)

Figure 14 indicates that the average BIA score is lower compared to the manufacturing peers (Luftman and Kempaiah, 2007) on all criteria with an average difference of 0.56.

• The maximum delta is for value measurement (0.78) which was not expected considering IT is

outsourced already, but the contract value follow up is unclear. Apparently the value measurement criteria can be improved significantly (“IT spend reporting is a serious issue and limits the trust”).

Criteria Aver Peers Delta

Communications 2.52 3.22 0.70 Value measure 2.32 3.10 0.78 Governance 2.94 3.15 0.21 Partnership 2.74 3.30 0.56 Scope and Arch. 2.73 3.17 0.44 Skills and comp. 2.20 2.90 0.70

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• The minimum delta is for governance (0.21) which is just below the peer average meaning this criteria is performing almost as expected for a manufacturing company. Interestingly this is not experienced by the business as indicated in the comparison between business and IT previously (“the informal organization is more effective than the formalised mechanisms and governance”). An observation is the fluctuation between the scores of the six maturity criteria. According to Luftman and Kempaiah (2007) the scores of companies with a more matured BIA (around 3) the differences between the six criteria are small which is reflected in the peers column. This is obviously not the case for Tata Steel Europe with a maximum average score of 2.94 for governance and a minimum average score of 2.20 for skills and competences, and this fluctuation suggests that the BIA is not very mature. Please note that the research of Luftman and Kempaiah (2007) did not make a distinction for companies who outsourced their IT, it was a general mix of companies from which is known that for manufacturing companies approximately 25% outsource their IT (Gartner, 2014A). More recent research (Luftman, 2014A) indicated that the manufacturing peer average has an almost identical maturity score with 3.17 with a minimum variation per individual criteria. This indicates that the BIA of manufacturing companies remained stable between 2007 and 2014 which is surprising considering the credit crunch in this period.

5.2.2 Business IT alignment all cases

To apply the maturity model of Luftman (2000) one single questionnaire (n=1) has been conducted per individual company from a senior IT manager. This makes the statistical relevance less reliable than the average of Tata Steel Europe (“Snakeboat”) were all fifteen questionnaire are averaged (n=15). The results of all eight cases are compared in figure 15 below.

Criteria Snakeboat Canoe Kayak Skiff Galley Sampan Gondola Longboat Max delta

Communications 2.52 3.00 2.50 2.33 3.33 3.00 1.83 4.00 2.17 Value measure 2.32 2.29 2.14 2.29 3.43 2.29 1.14 2.71 2.29 Governance 2.94 3.86 3.29 2.14 3.43 2.43 2.14 4.29 2.14 Partnership 2.74 2.83 3.33 2.17 3.00 2.33 1.50 3.33 1.83 Scope and Arch. 2.73 3.20 2.60 1.80 4.20 2.40 2.20 3.80 2.00 Skills and comp. 2.20 2.29 3.00 1.71 2.71 2.14 1.86 3.43 1.71

Average 2.58 2.91 2.81 2.07 3.35 2.43 1.78 3.59 1.81

Figure 15: Comparing BIA maturity scores of all cases (n=8)

Figure 15 shows that the BIA score of all cases are diffused on individual criteria as well as the average scores. This is reflected in the max delta column indicating the difference between the maximum and minimum scores with an average max delta of 1.81.

Effect of IT outsourcing on business IT alignment in manufacturing companies

Master thesis Marcus M. Veen

(student nr. 10645144)

June 2015

Faculty of Science

Information Studies

track Business Information Systems

Prof. Dr. Tom van Engers

Effect of IT outsourcing on

business IT alignment

in manufacturing companies

Supervisors:

Business IT alignment is everyone rowing in the same direction

Abstract

Keywords

Table of contents

1 Introduction

2 Theoretical background

2.1

IT outsourcing

2.2

Business IT alignment

2.3

Possible influencing factors

3

Methodology

3.1

Problem discussion

3.2

Approach

3.3

Research question

3.4

Research design

3.5

Case selection

4

Conceptual framework

4.1

Derksen research model

4.2

Research measurements

4.3

Research results

4.4

Research opportunities

5 Analysis and results

5.1

High level company description

5.2

Business IT alignment maturity results