Alignment definitions
Alignment has been conceptualized in the academic literature in various ways. Sauer and Yetton (1997) argue that its basic principle is that IT should be managed in a way that mirrors management of the business.Footnote 4 Reich and Benbasat (1996) define alignment as the degree to which the mission, objectives, and plans contained in the business strategy are shared and supported by the IT strategy. Henderson and Venkatraman (1993) state that alignment is the degree of fit and integration among business strategy, IT strategy, business infrastructure, and IT infrastructure. McKeen and Smith (2003) argue that strategic alignment of IT exists when an organization's goals and activities and the information systems that support them remain in harmony. Good alignment means that the organization is applying appropriate IT in given situations in a timely way, and that these actions stay congruent with the business strategy, goals, and needs (Luftman and Brier, 1999).
When asking focus group participants to define alignment, Campbell (2005) was given the following answer: ‘Alignment is the business and IT working together to reach a common goal.’ Similarly, Abraham (2006) described alignment using a rowing analogy; ‘Strategic alignment, is then, everyone rowing in the same direction.’ These perspectives do not refer to visions, strategies, plans, structures, etc. that are mentioned in many academic definitions of alignment but their meaning is very clear. However, because of their lack of precision, they are less helpful in articulating what exactly constitutes good alignment and how it might be measured.
Equivalent terms
In the literature, alignment has also been called fit (Chan, 1992; Henderson and Venkatraman, 1993), linkage (Reich, 1993), and integration (Henderson and Venkatraman, 1993). Chan (1992) defined fit as the degree of coherence between realized business strategy and realized IT strategy. Henderson and Venkatraman (1993) defined fit in terms of the relationship between external business strategy and internal infrastructure and processes. They defined functional integration in terms of the business–IT relationship. Reich and Benbasat (1996, p. 56) defined linkage as ‘the relationship between the business domain and the IT domain’. These terms and others (e.g., bridge (Ciborra, 1997), harmony (Luftman et al., 1999), and fusion (Smaczny, 2001)) are sometimes used interchangeably with alignment although subtle differences exist.
The term ‘fit’ has an extensive research stream in the mathematical and strategic management literatures (e.g., see Edwards, 1992). In the MIS literature, it has often, but not exclusively, been used to refer specifically to the measurement of alignment (e.g., Bergeron et al., 2001). Although it may be argued that ‘alignment’ is now the dominant term in the MIS literature, this cannot be said for the strategy literature where we also find extensive use of terms such as fit, congruence, and covariation.
Alignment dimensions
In the MIS literature, several dimensions of alignment are clearly apparent: strategic/intellectual, structural, social, and cultural. Although significantly more attention is given to strategic IT alignment, both strategic alignment and structural alignment influence performance. In addition, alignment is contingent on many of the social and cultural aspects of an organization (Reich and Benbasat, 1996; Chan, 2001).
Strategic and intellectual dimensions
Strategic alignment refers to the degree to which the business strategy and plans, and the IT strategy and plans, complement each other. Reich and Benbasat (2000) define intellectual alignment in terms of ‘the state in which a high-quality set of inter-related IT and business plans exist.’ With this perspective, it is difficult for alignment to occur if the business lacks a formal, documented plan (Vitale et al., 1986; Lederer and Mendelow, 1989; Wang and Tai, 2003).
Kearns and Lederer (2000) argue for a distinction between the information systems plan (ISP)–business plan (BP) and BP–ISP model of alignment. The ISP's alignment with the BP, or the ISP–BP model, signifies IS management's understanding of business strategy (Reich and Benbasat, 1996). The BP–ISP alignment model, on the other hand, ensures that the business plan reflects the experience and knowledge of the organization utilizing IT-based resources, and signifies better top management understanding and commitment (Bensaou and Earl, 1998).
Structural dimensions
Structural alignment refers to the degree of structural fit between IT and the business. Structural alignment is influenced by the location of IT decision-making rights, reporting relationships, (de)centralization of IT, and the deployment of IT personnel (Chan, 2002). Pyburn (1983) found that IT is much more likely to be perceived as supporting the critical needs of the business when there are few levels between senior management and IT management.
Earl (1989) outlined five ideal IT arrangements: centralized, business unit, business venture, decentralized, and federal. In this model, ‘arrangement’ connotes the structures, processes, and accommodations that evolve when organizing IT. These arrangements need to be aligned with factors such as the host organization characteristics, technology assimilation, the strategic impact of IT, and the IT heritage.
Brown and Magill (1994) suggested a simpler structural typology involving IT structures that are centralized, decentralized, or hybrid. They provided evidence that each structure can be effective, given the right circumstances. In their study, the choice of a decentralized IT structure was influenced by a corporate strategy of unrelated diversification, a decentralized overall firm structure, a culture of strong autonomy without the desire for a CIO, satisfaction with the management and use of technology, and total business unit control over system approvals. The choice of a centralized IT structure resulted from a corporate strategy of related diversification, an overall firm structure of hybrid strategic business units, a culture of central direction, a CIO who was part of the top management team, satisfaction with the management and use of technology, and some business unit control of systems approvals.
Empirically, Tavakolian (1989) found that IT structure is strongly related to competitive strategy. That is, firms that have a conservative strategy tend to have a centralized IT structure. Those firms that are more entrepreneurial and risk-taking tend to have a decentralized IT structure. Bergeron et al. (2001) found that increasing structural complexity alone has no impact on performance. That is, more complex IT structures are not necessarily superior. However, increasing structural complexity in conjunction with a stronger IT management can increase competitive positions in terms of growth and profitability.
The informal structure
Although the formal structure is most often researched, Chan (2001) found the informal structure to be of great importance in improving IT alignment and performance. The informal structure was defined as ‘relationship-based structures that transcend the formal division of labor and coordination of tasks’. Chan's study suggested that scarce management time and resources are better spent on improving the informal organization than on aligning formal structures. Although less visible than the formal structure, it can be more malleable and paradoxically more enduring.
Social dimension
Reich and Benbasat (2000) define the social dimension of strategic alignment in terms of ‘the state in which business and IT executives within an organizational unit understand and are committed to the business and IT mission, objectives, and plans.’ They argue that researchers should study the social and intellectual dimensions of alignment together. This will reveal the complexity and challenges of IT alignment.
There are many barriers to achieving both intellectual and social dimensions of alignment and the prerequisite strong CEO–CIO relationship (Feeny et al., 1992). IT personnel and business staff must collaborate together at all levels of an organization. This is a prerequisite for high alignment. Yet this may be hindered by many issues such as the invisibility of the IT staff, communication barriers, history of IT/business relationships, attitudes of organization members to IT, shared domain of knowledge, and leadership (Earl, 1989; Campbell, 2005).
Cultural dimension
Pyburn (1983), in an early study on strategic IT issues, points out the importance of cultural fit between business and IT as a precondition for successful IS planning. He argues that IS planning can validly adopt a personal-informal or a written-formal approach, but that it needs to be aligned with cultural elements such as the business planning style and the top management communication style to be effective.
In essence then, alignment needs to be culturally supported; otherwise, it is a never-ending quest. Chan (2002) suggests that a strong company culture is a precondition to the type of informal structure that fosters alignment. Tallon (2003) emphasizes the need for a mind-set that encourages shared networks and common IT procurement policies, and an across-the-board willingness to give up incompatible best-of-breed systems. He states that the ‘alignment paradox’ cannot be avoided just by picking certain technologies and avoiding others. Flexibility takes vigilance and smart management approaches.
Alignment is then fundamentally about cultural change and behavior change (CIO Insight Staff, 2004). There has to be commitment from top management for alignment to work. People are not going to listen to what the CIO says as much as they are going to watch what the CIO does, and what the CIO's business partners do. IT personnel need to be skilled in the softer side of business, which often does not go hand-in-hand with the engineering focus of IT professionals. Top management buy-in, proactive CIOs, and socially adept IT professionals are vital for making alignment a cultural phenomenon.
Van Der Zee and de Jong (1999) and CIO Insight Staff (2004) raise the issue of the lack of a common ‘language’ between business and IT executives. They cite the need to build bridges so that both IT and business personnel are using the same terms, talking about the same topic, which in turn assists with alignment in thought and action. Hunt (1993) states that in well-aligned firms, top management welcomes what can be done through IT, using their understanding of the particular business issues in their company and their imagination when conceiving IT-enabled business strategies.
Burn (1993) advocates a cultural audit to examine the relationships between organizational and IT strategy formulation processes. Burn suggests two independent audit checks: one to review the alignment of organizational strategy and structure, and the other to review the alignment of IT strategy and structure. The two audit checks, when applied together, are referred to as the organizational ‘cultural’ audit framework.
Levels of alignment
Ideally, alignment should be present at all levels of the organization, including the organizational level, system level (Floyd and Woolridge, 1990; Campbell, 2005), project level (Jenkin and Chan, 2006), and the individual/cognitive level (Tan and Gallupe, 2006).
According to Floyd and Woolridge (1990), misalignment can often explain system implementation difficulties. Formal strategies are often only implemented at the upper levels of the organizations, yet strategy is carried out on the front line. The focus of alignment at the lower levels of an organization involves translating business unit goals into personal goals (Campbell, 2005).
Recognizing this problem, Bleistein et al. (2006) attempt to use requirements engineering to link higher-level strategic goals to lower level, explicit organizational processes. Their model provides a mechanism for verifying alignment as requirements are explicitly verified with super-ordinate goals and subordinate goals.
Jenkin and Chan (2006) examine alignment at the project level. They define IT project alignment as the degree to which an IT project's deliverables are congruent with the organization's IT strategy and the project's objectives. Critical to project alignment is the project's response to change triggers. These triggers can be both internal (e.g., a mid-term project evaluation) and external (e.g., a change in the operating environment). Failure to respond to change triggers effectively leads to project misalignment. Project misalignment can trickle upwards, leading to overall IT strategic misalignment.
Tan and Gallupe (2006) operationalize alignment, at its most micro-level, as shared cognition between the business and IT executives. That is, the higher the level of cognitive commonality between business and IT executives, the higher the levels of IT–business alignment. Similarly, the greater the diversity in the cognitive structure and content of business and IT executives, the lower the expected levels of alignment. This perspective has strong parallels with the social dimension of alignment, based on shared domain knowledge (Reich and Benbasat, 2000). It also reflects a view of business–IT alignment in which IT mirrors (vs challenges) ongoing business activities.
Internal vs external alignment
Earl (1989) proposes that IT strategy and infrastructure should be aligned with information systems strategy (i.e., the applications and information) within an organization. Henderson and Venkatraman (1993) assert that alignment must be both internal and external to the organization. Externally, organizations must align their business and IT strategies with industry and technology forces while internally organizations must align organizational and IT processes and infrastructure. Sledgianowski and Luftman (2005) recommend as an alignment best practice that organizations should leverage IT assets on an enterprise-wide basis to extend the reach (the IT extrastructure) of the organization into supply chains of customers and suppliers. Similarly, Galliers (2004) suggest that alignment is not just related to internal challenges, but should also influence and be influenced by relationships with crucial partner organizations such as customers and suppliers.
Alignment measures
The measurement of alignment is important for several reasons. For practitioners, if alignment can be measured, it can more readily be managed. For academics, reliable and valid measures are important if alignment investigations are to be rigorous. In the MIS literature, several different approaches have been used to assess alignment, including typologies and taxonomies, fit models, survey items, mathematical calculations, and qualitative assessments. These are outlined below.
Typologies and taxonomies
While typologies are deductive, intuitive groupings or classifications of phenomena, taxonomies are groupings based on the results of inductive, empirical analyses (Chan, 1992). Sabherwal and Chan (2001) use the Miles and Snow (1978) strategy typology to measure business strategy, predict the appropriate IT strategy, and assess alignment. For Defenders (see Miles and Snow, 1978), they expected theoretically to see ‘alignment for IS efficiency’, for Prospectors, they anticipated ‘alignment for IS flexibility’, and for Analyzers, the expectation was ‘alignment for IS comprehensiveness’. They were able to compute detailed typology-based alignment assessments when they empirically examined real-life business and IT strategies. Using similar mathematical techniques, Sabherwal and Kirs (1994) demonstrate how to compute misalignment, the opposite of alignment, using weighted Euclidean distances of IT capability variables from an ideal profile.
Different fit models
Venkatraman (1989) discusses six different conceptualizations of fit in strategy research:
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moderation – calculated using interaction terms
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mediation – modeled using indirect or intermediate variables
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matching – measured using difference scores
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gestalts – arrived at via cluster analysis
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profile deviation – examined using pattern analysis
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covariation – computed using factor analysis.
Bergeron et al. (2001) examine these six conceptualizations of fit in IT research. They argue that studies which neglect to specify the exact perspective of fit may lead to contradictory, mixed, or inconsistent results (Bergeron et al., 2004). In addition, specifying one type of fit conceptually and then using measures designed for another type of fit introduces errors. Cragg et al. (2002) provide evidence of inconsistent results from two different measurement approaches, the matching perspective and the moderation perspective. They also argue the importance of selecting appropriate alignment models.
Chan et al. (1997) developed the STROIS (Strategic Orientation of IS) instrument based on an earlier STROBE (Strategic Orientation of Business Enterprises) instrument by Venkatraman (1989). The Chan et al. (1997) study provides empirical support for modeling IT strategic alignment using a moderation or synergistic approach rather than a simple matching or mirroring approach. Assessing the alignment of business strategy and IT strategy based on the combination of STROBE and STROISFootnote 5 has subsequently been carried out by others (e.g., Ma and Burn, 1998; Cragg et al., 2002). In the Cragg et al. (2002) study, to maximize related benefits, IT alignment was modeled as the interaction between business strategy and IT strategy (i.e., as a moderation variable), rather than as a simple match between the two.
Questionnaire items : Many IT studies have simply posed the question, ‘On a scale of 1–5, how do you rate IT alignment in your organization?’ While this can be helpful as a single indicator of overall alignment, more detailed scales provide greater reliability and validity. Kearns and Lederer (2003) developed a 12-item measure of alignment. This scale measures the alignment of the IT plan with the business plan (six items) and the alignment of the business plan with the IT plan (six items). Bergeron et al. (2004) developed a questionnaire to measure IT strategy and IT structure. Their measure included dimensions of IT environment scanning, IT planning and control, and IT acquisition and implementation. After testing 66 initial items, a final measure of 29 items was retained.
The Organizational Culture Audit (OCA) is another questionnaire-based method for measuring alignment (Burn, 1993, 1996). As alignment is an ongoing process, the OCA instrument is completed annually by different managers. This yearly review and change in respondents’ opinions provide a robust picture of alignment in an organization. Six relationships in particular are examined: the external strategy and the IT strategy, the internal-infrastructure model for business and IT, and planning models for internal and external cross-alignment.
Other mathematical calculations and models : There are many other quantitative mechanisms to assess alignment in the literature. For instance, Day (1996) argues for the following three measures:
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Alignment measurements – Alignment indices that are used to determine how effectively the IT function is supporting the company's overall goals at the strategic level.
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Alignment index – A simple comparison of the IT activities to stated business goals. In making the comparison, a percentage value should be assigned, based on a scale of 1–100, that represents the subjective evaluation of how well aligned each activity is with the business objective it supposedly serves.
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Effectiveness acid test – A direct comparison between the proportion of IT expenditures devoted to specific P&LFootnote 6 line activities and the volume of each activity expressed as a percentage of sales. These two figures should be similar in magnitude over time.
It is not possible to completely list the quantitative models and tests of alignment used in research and industry. The authors welcome details of these tests and hope to make them available to future readers with the assistance of the Journal of Information Technology.
Qualitative measures : To complement quantitative assessments, researchers and practitioners make rich, qualitative judgments regarding the state of IT alignment in organizations. Reich and Benbasat (1996) compare several measures of the social dimension of alignment, including alignment of written business and IT plans, self-reports, mutual understanding of current objectives, and congruence in long term business and IT visions. They validate two out of four proposed measures of linkage, namely understanding of current objectives (short term alignment) and congruence in IT vision (long term alignment). In their study, written IT and/or business plans often did not exist and self-reports needed to be used with caution.
Psychological measures : Tan and Gallupe (2006) examine shared cognition as a proxy for alignment. Using cognitive maps between business and IT executives (Tan and Hunter, 2002), they find that higher cognitive commonality is related to higher levels of alignment.
Alignment models
While measures are granular and descriptive, we view models as more holistic and prescriptive. In this section, we present only the few alignment models that have been particularly influential. We focus on a stream of research emerging in parallel from North America and Europe in the early 1990s. Many studies since then have used concepts from these models. Because of space constraints, several other important models have not been described.Footnote 7
Initially, IT served primarily in a ‘back office’ or support role capacity. However, with the advancement of technology, many saw the potential for IT to perform a more strategic function. Research conducted in the 1980s at MIT (Scott Morton, 1991) served as an initial attempt to harness the strategic power of IT. The MIT model (see Figure 1) argues that revolutionary change involving IT investment can bring about substantial rewards as long as the key elements of strategy, technology, structure, management processes and individuals and roles are kept in alignment.
Henderson and Venkatraman (1992) were influenced by the MIT research in their creation of the Strategic Alignment Model (SAM), which is perhaps the most widely cited of all alignment models.Footnote 8 The SAM model is based on four related key domains of strategic choice, namely business strategy, organizational infrastructure and processes, IT strategy, and IT infrastructure and processes (see Figure 2).
In the SAM model, the concept of strategic alignment is distinct from bivariate fit (i.e., linking only two domains) and cross-domain alignment (i.e., linking any three domains). A distinction is also drawn between the external perspective of IT (IT strategy) and the internal focus of IT (IT infrastructure and processes). The potential of IT to both support and shape business policy is recognized (Henderson and Venkatatram, 1992).
The SAM model has received empirical support and has conceptual and practical value (Goedvolk et al., 1997; Avison et al., 2004). However, it has its limitations. For instance, depending on how IT-intensive an industry is, the model's applicability may vary, as the assumptions of the SAM model may not hold (Burn and Szeto, 2000).
Several scholars have built on and extended the SAM model (e.g., Luftman et al., 1993). Goedvolk et al. (1997) extend the SAM model by focusing on technical and architectural requirements. Avison et al. (2004) add to the SAM model, providing managers and researchers with additional practical ways to attain alignment. They advocate examining projects worked on over a previous period, and in this way retrospectively determining alignment. This approach can be used to monitor alignment, pre-empt a change in strategy and implement a new alignment perspective by re-allocating project resources.
Maes (1999) and Maes et al. (2000) also extend the SAM model, producing a framework that incorporates additional functional and strategic layers. They separate information providers from the systems that provide information. A new information domain represents the knowledge, communication and coordination of information. They also add a third dimension that contains specific sub-architecture areas.
The MacDonald (1991)Footnote 9 model, building on MIT 1990s Framework also examines inter-relationships between business and IT strategy, infrastructure and processes. External impacts on customers, suppliers, and markets are considered. MacDonald argues that in order to achieve alignment, various cycles must be run. In cycle 1, the stages include competitive potential, business value, service level, and technology potential. In cycle 2, the stages created in cycle 1 are reviewed.
Baets (1992) developed a model of alignment adapted from the alignment models of MacDonald (1991) and the enterprise-wide information model (Parker et al., 1988). Like the SAM model, it depicts the interaction of business strategy, organizational infrastructure and processes, IS infrastructure and processes, and IT strategy (see Figure 3). Baets's model also recognizes that alignment takes place in a broader context and incorporates factors such as competition, organizational change, human resource issues, the global IT platform, and IS implementation processes.
Baets (1992) does challenge a SAM assumption of participant awareness of the economic environment and the corporate strategy. He argues that in most organizations, there is not a monolithic, widely accepted strategy and further, that most organizational members do not know the strategy.
It is not surprising that the Baets (1992), Henderson and Venkatraman (1992), and MacDonald (1991) models have strong similarities. At their roots lie the MIT Framework of the 1990s and the strategic IS planning literature (e.g., Galliers, 1988).
The alignment models presented here are just a small (albeit important) sample of the several models in the literature today. Readers wishing to have information on other models are invited to examine the Annotated Scholarly Bibliography of IS Alignment Research also published in this issue of the Journal of Information Technology.