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The Creation of Business Architecture Heat Maps to Support Strategy-aligned Organizational Decisions

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The Creation of Business Architecture Heat Maps to Support Strategy-aligned Organizational Decisions

Abstract and Figures

The realization of strategic alignment within the business architecture has become increasingly important for companies. Indeed, it facilitates business-IT alignment as a well-designed business architecture helps both to identify the appropriate requirements for IT systems and to discover new business opportunities that can be realized by IT. However, there is a lack of alignment techniques that support organizational (re)design decisions during the operation phase as the actual performance of business architecture elements is neglected. Capability heat maps provide a useful starting point in this respect as they focus on the creation of a hierarchy of prioritized capabilities, which are characterized by a performance measure. In this paper, these techniques will be extended to support strategy-aligned decisions within the business architecture. The identification of the relevant business architecture elements is based on state-of-the-art enterprise modelling languages, which enable the development of enterprise models on distinct layers of the business architecture. Strategic alignment between these elements will be realized by using prioritization according to the Analytic Hierarchy Process (AHP), while performance measurement will enable the creation of a proper decision support system. Afterwards, the proposed heat map will be applied on a case example to illustrate its potential use. This results in the completion of a first build-and-evaluate loop within the Design Science methodology.
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The Creation of Business Architecture Heat Maps to Support Strategy-aligned Organizational
Decisions
Ben Roelens, Geert Poels
Department of Management Information Science and Operations Management
Faculty of Economics and Business Administration, Ghent University, Gent, Belgium
Ben.Roelens@UGent.be
Geert.Poels@UGent.be
Abstract: The realization of strategic alignment within the business architecture has become
increasingly important for companies. Indeed, it facilitates business-IT alignment as a well-designed
business architecture helps both to identify the appropriate requirements for IT systems and to
discover new business opportunities that can be realized by IT. However, there is a lack of alignment
techniques that support organizational (re)design decisions during the operation phase as the actual
performance of business architecture elements is neglected. Capability heat maps provide a useful
starting point in this respect as they focus on the creation of a hierarchy of prioritized capabilities,
which are characterized by a performance measure. In this paper, these techniques will be extended
to support strategy-aligned decisions within the business architecture. The identification of the
relevant business architecture elements is based on state-of-the-art enterprise modelling languages,
which enable the development of enterprise models on distinct layers of the business architecture.
Strategic alignment between these elements will be realized by using prioritization according to the
Analytic Hierarchy Process (AHP), while performance measurement will enable the creation of a
proper decision support system. Afterwards, the proposed heat map will be applied on a case
example to illustrate its potential use. This results in the completion of a first build-and-evaluate loop
within the Design Science methodology.
Keywords: Business architecture, Heat maps, Enterprise modelling, AHP, Performance
measurement
1. Introduction and background
The realization of strategic alignment within the business architecture of an enterprise is important to
understand the complex business context, which is sustained and possibly enhanced by information
systems to realize Business-IT alignment (Pijpers et al. 2012). Indeed this ensures that information
systems contribute to processes, which support the organizational goals, and to the resulting value
creation for the company and its various stakeholders (Andersson et al. 2009).
The business architecture concept originates from the enterprise architecture field, which is a holistic
approach offering an integrative view on the company. This includes the use of models, besides other
principles and methods, to design and realize the business architecture, information systems
architecture, and technology architecture (Lankhorst 2009). Enterprise models contribute to the
design of the business architecture by three types of models: goal, value, and process models
(Andersson et al. 2009, Pijpers et al. 2012). While goal models address the why perspective within a
company, value models focus on what a company must do to implement organizational goals with the
aim of value creation. Process models specify how value should be created by defining process
activities and individual responsibilities at the operational level.
Related research (see review in Roelens and Poels (2013a)) tried to realize strategic alignment
between goal, value, and/or process models. Most of these efforts focus on top-down strategic
alignment by developing transformation rules based on mappings between the meta-model constructs
of the different model types. Other authors (see Buder and Felden (2012)) used annotation to enrich
process models with value or goal information to establish a bottom-up strategic alignment. Although
all these approaches ensure the consistency between enterprise models, they only offer a static view
on the enterprise as the actual performance is neglected. As such, these techniques are useful during
the design phase of the business architecture, but they do not support organizational (re)design
decisions taken during the actual operation of the company.
This research gap will be addressed by the development of a business architecture heat map, which
combines the use of AHP, to ensure top-down strategic alignment between the business architecture
elements by prioritization, with performance measurement principles to facilitate the support of
organizational (re)design decisions.
The paper is structured as follows. Section 2 describes the creation of the business architecture heat
map based on literature about business architecture elements and the creation of heat maps. Section
3 provides a demonstration by a case example, while section 4 briefly discusses future research.
2. Business architecture heat map
2.1 Business architecture elements
The meta-model model elements (figure 1) are related to the perspectives within the business
architecture. Goals (i.e., the why perspective) are classified as either financial, customer, or internal
indicators (Kaplan and Norton 1992). Learning and growth objectives are not included as the
developed heat map supports strategy-aligned decisions within the existing business architecture,
rather than changing it through innovation. To address the what perspective, a literature review was
used about the constituting elements of the business model concept (Roelens and Poels 2013b). The
financial structure of a company is a representation of the costs from acquiring resources and the
revenues earned from the offered value proposition (Roelens and Poels 2013b). Hence, the value
stream starts from the financial goals via the financial structure to the value proposition of a company.
Since the value proposition is the set of products and services, which provides value to the customers
of a company (Roelens and Poels 2013b), this concept is the implementation of the customer
objectives in the business architecture. The value stream continues from both the value proposition
and the internal objectives to the core competences and the value chain. The value chain is an
aggregation of the elementary value-contributing activities of an organization. These activities address
the how perspective in the business architecture and are the end of the value stream.
Figure 1: Meta-model of the business architecture heat map
2.2 Heat map
To create the heat map, the value stream relations between the elements are characterized by an
importance (figure 1). This allows specifying distinct priorities in case an element supports different
upper elements (e.g., a process contributing to two core competences). AHP is proposed to prioritize
between the different business architecture elements as it deals with inconsistencies that are inherent
to subjective judgements (Hafeez et al. 2002). To obtain the priorities, pairwise comparisons are
made between those elements that have the same upper element in the value stream. This
comparison is performed on a 9-point scale (Saaty 2008), ranging from 1 (i.e., two elements
contribute equally to the above element) to 9 (i.e., the evidence of favouring one element over another
is of the highest possible order of affirmation), and results in the creation of a comparison matrix. The
resulting priorities are given by the real eigenvector of this matrix. Afterwards, the lowest priority is
rescaled to 1 to account for differences in the number of child elements of a certain upper element.
The colour of the value stream relationship depends on whether it is characterized by a high (i.e., ≥ 5
visualized in (solid) red), medium (i.e., ≥ 3 and < 5 visualized in (dashed) orange), or low importance
(i.e., < 3 visualized in (pointed) green).
The use of performance measurement enables the analysis of the actual performance of the business
architecture elements. This includes the specification of a measure for each of these elements.
Measures are characterized by a description, a performance goal, a deviation %, and the actual
performance (figure 1). Depending on the actual performance, the colour of the business architecture
elements is either (solid) red (i.e., < performance goal x (1 deviation %)), (dashed) orange (i.e.,
performance goal x (1 - deviation %) and < performance goal x (1 + deviation %)), or (pointed) green
(i.e., ≥ performance goal x (1 + deviation %)). By a proper use of the measure attributes, it is possible
to deal with both quantitative and qualitative measures (table 1).
Table 1: Measures supported by the business architecture heat map
Type
Example
Performance
goal
Deviation %
Actual
performance
Positive quantitative measure
Profit
g
d
a
Negative quantitative measure
Loss
1/g
-d/(1-d)
1/a
Qualitative measure
Satisfied
criterion
1=yes
0
0=no or 1=yes
3. Case example
This case example describes the business architecture of a fictitious bakery, facing a declining
customer loyalty. Based on the data model (figure 2), it is possible to develop the business
architecture heat map (figure 3) according to the described procedure. Due to limited space, the
comparison matrices of the AHP are omitted and only the resulting priorities are given.
Figure 2: Data model supporting the case example
Several insights emerge from the developed heat map. The critical path to increase customer loyalty
is constituted by value stream relations that are characterized by a medium or high importance. Within
this path, attention must be given to elements with a bad performance (i.e., the activity of preheating).
In practice, a buzzer indicates when dough can be put in the oven. However, due to the time that is
needed to put the dough in the oven, the temperature gets too high. This increases the number of
collapsing breads after baking. By adapting the preheating activity, improvements can be made to
offer higher quality products and to increase customer loyalty.
Another analysis is based on elements with a bad performance that are not on a critical path (i.e., fill
in evaluation forms). As this activity is not the main driver for the core competence of resource
sourcing, it should be questioned whether to perform this activity in-house. A solution includes asking
suppliers to perform the quality checks themselves and to provide certificates. Another improvement
is to incorporate quality checks in the performance evaluation of the responsible employees. This
should improve the awareness for this activity in the workplace.
Figure 3: Business architecture heat map applied on the case example
4. Discussion
This paper completes a first step in the development of a strategic decision support system. Future
research includes applying the proposed heat map by practical case study research to evaluate the
meta-model and its visualization. This evaluation will provide support for the claimed benefits of the
business architecture heat map in comparison to the existing techniques. An important benchmark in
this respect is the Business Intelligence Model (Horkoff et al. 2014), which also uses performance
measures to align activities with strategic objectives. However, the approach is different as
performance measures are exclusively used on the level of activities, which prevents the creation of
visual heat maps. The evaluation also requires the development of tool support, which facilitates the
large-scale creation of business architecture heat maps that can easily be exchanged between
business users.
5. References
Andersson, B., Johannesson, P. and Zdravkovic, J. (2009) Aligning Goals and Services through Goal
and Business Modelling. Information Systems and e-Business Management, Vol 7, No. 2, pp 143-
169.
Buder, J. and Felden, C. (2012) Towards a Reference Model of Business Model & Business Process
Management Alignment. 6th International Workshop on Value Modeling and Business Ontology,
February 20-21, 2012, Vienna, Austria.
Hafeez, K., Zhang, Y. and Malak, N. (2002) Determining Key Capabilities of a Firm Using Analytic
Hierarchy Process. International Journal of Production Economics, Vol 76, No. 1, pp 39-51.
Horkoff, J., Barone, D., Jiang, L., Yu, E., Amyot, D., Borgida, A. and Mylopoulos, J. (2014) Strategic
Business Modeling: Representation and Reasoning. Software & Systems Modeling, Vol 13, No. 3, pp
1015-1041.
Kaplan, R. and Norton, D. (1992) The Balanced Scorecard - Measures That Drive Performance.
Harvard Business Review, Vol Jan-Feb, pp 71-79.
Lankhorst, M. (2009) Enterprise Architecture at Work: Modelling, Communication and Analysis,
Springer-Verlag, New York.
Pijpers, V., de Leenheer, P., Gordijn, J. and Akkermans, H. (2012) Using Conceptual Models to
Explore Business-ICT Alignment in Networked Value Constellations. Requirements Engineering, Vol
17, No. 3, pp 203-226.
Roelens, B. and Poels, G. (2013a) Towards a Strategy-Oriented Value Modeling Language:
Identifying Strategic Elements of the VDML Meta-Model. In: Ng, W., Storey, V.and Trujillo, J., eds.
32nd International Conference on Conceptual Modeling, Hong Kong, China: Springer-Verlag, pp 454
462.
Roelens, B. and Poels, G. (2013b) Towards an Integrative Component Framework for Business
Models: Identifying the Common Elements between the Current Business Model Views. In:
Deneckère, R.and Proper, H., eds. CAiSE'13 Forum at the 25th International Conference on
Advanced Information Systems Engineering, Valencia, Spain, pp 114-121.
Saaty, T. (2008) Decision Making with the Analytic Hierarchy Process. International Journal of Service
Sciences, Vol 1, No. 1, pp 83-98.
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Executives know that a company's measurement systems strongly affect employee behaviors. But the traditional financial performance measures that worked for the industrial era are out of sync with the skills organizations are trying to master. Frustrated by these inadequacies, some managers have abandoned financial measures like return on equity and earnings per share. "Make operational improvements, and the numbers will follow,"the argument goes. But managers want a balanced presentation of measures that will allow them to view the company from several perspectives at once. In this classic article from 1992, authors Robert Kaplan and David Norton propose an innovative solution. During a yearlong research project with 12 companies at the leading edge of performance management, the authors developed a "balanced scorecard;" a new performance measurement system that gives top managers a fast but comprehensive view of their business. The balanced scorecard includes financial measures that tell the results of actions already taken. And it complements those financial measures with three sets of operational measures related to customer satisfaction, internal processes, and the organization's ability to learn and improve-the activities that drive future financial performance. The balanced scorecard helps managers look at their businesses from four essential perspectives and answer Some important questions. First, How do customers see us? Second, What must we excel at? Third, Can we continue to improve and create value? And fourth, How do we appear to shareholders? By looking at all of these parameters, managers can determine whether improvements in one area have come at the expense of another. Armed with that knowledge, the authors say, executives can glean a complete picture of where the company stands-and where it's headed.
Book
An enterprise architecture tries to describe and control an organisation's structure, processes, applications, systems and techniques in an integrated way. The unambiguous specification and description of components and their relationships in such architecture requires a coherent architecture modelling language. Lankhorst and his co-authors present such an enterprise modelling language that captures the complexity of architectural domains and their relations and allows the construction of integrated enterprise architecture models. They provide architects with concrete instruments that improve their architectural practice. As this is not enough, they additionally present techniques and heuristics for communicating with all relevant stakeholders about these architectures. Since an architecture model is useful not only for providing insight into the current or future situation but can also be used to evaluate the transition from 'as-is' to 'to-be', the authors also describe analysis methods for assessing both the qualitative impact of changes to an architecture and the quantitative aspects of architectures, such as performance and cost issues. The modelling language and the other techniques presented have been proven in practice in many real-life case studies. So this book is an ideal companion for enterprise IT or business architects in industry as well as for computer or management science students studying the field of enterprise architecture.
Book
An enterprise architecture tries to describe and control an organisation's structure, processes, applications, systems and techniques in an integrated way. The unambiguous specification and description of components and their relationships in such architecture requires a coherent architecture modelling language. Lankhorst and his co-authors present such an enterprise modelling language that captures the complexity of architectural domains and their relations and allows the construction of integrated enterprise architecture models. They provide architects with concrete instruments that improve their architectural practice. As this is not enough, they additionally present techniques and heuristics for communicating with all relevant stakeholders about these architectures. Since an architecture model is useful not only for providing insight into the current or future situation but can also be used to evaluate the transition from 'as-is' to 'to-be', the authors also describe analysis methods for assessing both the qualitative impact of changes to an architecture and the quantitative aspects of architectures, such as performance and cost issues. The modelling language and the other techniques presented have been proven in practice in many real-life case studies. So this book is an ideal companion for enterprise IT or business architects in industry as well as for computer or management science students studying the field of enterprise architecture.
Article
Decisions involve many intangibles that need to be traded off. To do that, they have to be measured along side tangibles whose measurements must also be evaluated as to, how well, they serve the objectives of the decision maker. The Analytic Hierarchy Process (AHP) is a theory of measurement through pairwise comparisons and relies on the judgements of experts to derive priority scales. It is these scales that measure intangibles in relative terms. The comparisons are made using a scale of absolute judgements that represents, how much more, one element dominates another with respect to a given attribute. The judgements may be inconsistent, and how to measure inconsistency and improve the judgements, when possible to obtain better consistency is a concern of the AHP. The derived priority scales are synthesised by multiplying them by the priority of their parent nodes and adding for all such nodes. An illustration is included.