Business Value Creation through Business Processes Management and Operational Business Intelligence Integration

Transcription

1 Business Value Creation through Business Processes Management and Operational Business Intelligence Integration Olivera Marjanovic University of Sydney, Australia Abstract Current approaches to Business Process Management (BPM) and operational Business Intelligence (BI) integration have been very limited and simply reduced to the problem of technical integration between BPM and BI systems. This paper argues that further opportunities for business value creation could be discovered through systematic analysis of the non-technical aspects of BI and BPM integration, especially in terms of strategy alignment, human-centered knowledge management and ongoing improvement of BI supported processes. The paper proposes a theoretical framework founded in the related research in BPM, BI and Knowledge Management (KM) fields and describes how it has been used to guide our empirical case study research in service organisations in the context of BI-supported customer-facing processes. 1. Introduction An ever increasing volume of business data that a typical organisation needs to manage, analyse and ultimately turn into actions, has fast tracked the field of Business Intelligence to the top of the CIO s and CEO s priority lists worldwide [1]. While organisations with enterprise-wide data warehouses will continue to benefit from the strategic BI, in terms of longterm decision making support, dynamic nature of everyday business creates a need for a different type of tools to be placed in the hands of operational decision makers. Operational BI is now bringing powerful analytical tools from the back office and designated knowledge workers, to the front office and customer-facing employees, turning them into a new type of knowledge workers. Supported by BI tools that are giving them more insight into customers behaviour, these employees are now in a position to inject more personalised knowledge into their business processes (BP) making them harder to copy by their competitors. Operational BI builds on existing technology standards to make business intelligence more flexible, transparent and cost-effective, by tightly integrating BI with organisation s constantly evolving business processes [2]. Real-time decision support in the context of operational, customer-facing processes has created a pressing need for better understanding of BI and BP integration, especially in terms of value creation. The business value of BI lays in its use within management processes that impact on the operational processes which in turn, drive revenue or reduce costs, as well as in its use within those operational processes themselves [3]. As more organisations are gradually reaching a higher level of BI maturity, they are becoming increasingly aware that BI-supported BPs need to be managed, improved or even redesigned to take the full advantage of BI solutions. BI leaders are now starting to consider BP-related issues that have been the main focus of another field Business Process Management (BPM) for the last two decades. However, current consideration of BI and BPM integration has been very limited and reduced to technical integration between BI and BPM systems. This paper argues that further opportunities for business value creation could be discovered through systematic analysis of non-technical aspects of BPM and BI integration, especially in terms of strategy alignment, human-centered knowledge management and ongoing improvement of BI supported processes. The paper uses the exploratory case study research to investigate the non-technical patterns of BPM and operational BI integration, across people, processes and strategy components of a holistic BPM model. It focuses on the following research question: What are the existing non-technical patterns of BPM and Operational BI integration in the context of customer-facing BPs in service industries? /10 $ IEEE 1

2 The paper proposes a theoretical framework founded in the related research in BPM, BI and Knowledge Management (KM) fields and describes how this framework has been used to inform our empirical case study research in organisations that are currently using BI solutions to support their customer-facing BPs. In addition to its main research contribution in the form of a theoretical framework and an evolving set of integration patterns, this work also makes contributions to the current BPM and BI practice. It offers an evolving road map of BI and BPM integration that could be used by practitioners to guide their integration efforts beyond technology. 2. Background and motivation As the BPM and BI fields have reached a converging point, it has become evident that the respective views and understanding of the fundamental concepts such as business process, business intelligence or even business process intelligence are quite different. For example, in the field of BI, BPs are often reduced to fully automated, workflowsupported processes that were the main area of practice and research in the BPM field in the mid-90s. At the same time, BPM tends to reduce business data to the process data, mainly those captured and processed by the BPM systems. Furthermore, BPM and BI integration has been predominantly considered at the technical level and is often vendor driven. Without any doubt, technical integration is a complex problem. When solved properly, it brings value to organisations by helping them to turn insight into action that may result in significant efficiencies, increased responsiveness to the realtime problems and opportunities, and crossorganisational visibility [1]. Driven by the need to gain a better insight into operational BPs and better decision-support within these processes, technical integration efforts will continue, especially in organisations where BPM and BI are perceived to be technical areas. However, by focusing solely on the technical integration, organisations are yet to reach the full potential. For many companies, achieving operational BI simply means viewing operational data from their primary ERP system, namely SAP [4]. New insights and opportunities are created when the integration problem is extended beyond technology. First of all, BI-supported BPs need to be managed and continuously improved. While one could argue that BP improvement efforts should not be affected by the underlying BP-support technology, we argue that this is not the case with BI-supported operational BPs. As illustrated later in the paper, BI changes the nature of work for the process participants by giving them better insights and more opportunities to make their operational processes knowledge intensive. Consequently BI-supported BPs call for a different type of improvement methodology, with more emphasis placed on the experiential knowledge. In fact, even the term Business process is too generic or coarse-grinded when considered for the integration purposes. For example, primary BPs will require different type of integration than supporting BPs that could continue to benefit from the traditional BI reporting tools. Customer-facing BPs themselves will vary in terms of types of decisions involved and the level of expertise required, as well as the relationships between processes, information and decisions. Furthermore, the volume of business transactions, competitiveness of the given industry and the actual types of products and services will determine the nature of the customer-facing BPs and business value that could be generated through their integration with BI. For example, for companies competing on the bases of product differentiation, their need for BI integration will be very different than for those competing in highly commoditized industries. In the later case, a better customer insight provided by BI, will offer opportunities for differentiation on the basis of efficiency, and to some degree process personalization, even with large volumes of transactions. Integration of BPM and operational BI, also impacts on the people component, in particular training methods and strategies for sharing of best practices among customer-facing officers. These are especially needed for organizations aiming for more knowledge-intensive BPs. While both BI and BPM independently seek to align their strategies with the overall business strategy, BI and BPM integration in the context of operational BP, also requires their mutual alignment. For example, the BPM strategy considers the overall enterprise BP architecture and how different cross functional BPs fit together at the enterprise level. The BI strategy also looks at the big picture of enterprise-wide cross-functional integration, but through the lenses of data rather than processes. These different integration paradigms, data- versus process-centric, make the process of BI and BPM strategy realignment very challenging as 2

3 these viewpoints are often incompatible. Consequently, any integration effort requires a multi-perspective approach. However, as hard as it is, this integration is very important, especially in the case of customer-facing BPs. As organisations are learning more and more about their customers, through BI-enabled customer segmentation, cross-functional data integration gives a customer-facing employee a 360 view of the customer. At the same time, crossfunctional process integration enables implementation of customer-centered end-to-end processes and provides a context for more detailed customer analysis. Based on the above discussion, we argue that the BI/BPM integration needs to be considered beyond technology at the levels of strategy, people and processes, including their management, ongoing improvement and redesign. Therefore, it is necessary to adopt a holistic rather than a technical view. 3. Literature review A very comprehensive literature review confirms that the need for better integration of BPM and operational BI had been identified in the trade press long before it was considered by BI and BPM research communities. So far, this problem has been investigated mainly by the computer science researchers. For example various research projects focus on BP intelligence and implementation of BI tools on top of BPM systems (e.g. see [5] and [6]). Alternatively, BPM systems are used as one of the sources of enterprise data. This approach is very popular among BI vendors that tend to focus merely on adding process metrics to their product architecture for traditional reporting and analysis [5]. Process-related data are also provided by the BAM (Business Activity Monitoring) systems, even though these systems do not offer process management support as BPM systems. However, process-data provided by any BPM or BAM system, regardless of its level of sophistication, are only a subset of the overall enterprise-wide business data and therefore incomplete. While the CS community continues to explore the technical aspects of BP and BPM integration looking for example, for more efficient ways to integrate enterprise-wide data with rule-based workflows, better ways to mine and visualise process data and create more flexible decision support tools, the information systems (IS) community remains very much silent on the integration issue. A very comprehensive review of the current IS literature including the leading IS journals (A and A+), ISrelated specialist journals and IS conferences over the last five years, confirms a very large research gap. Excluding the papers that only mention BPs in the BI context and vice versa, BI and BPM integration has been broadly discussed only by few IS research papers, more as a side point and always from a single perspective (BPM or BI). This confirms that the area of BPM and BI integration, so far, remains virtually unexplored by the IS researchers. Having achieved technical integration, the companies are now facing the IS-related integration issues. In the absence of well established integration frameworks, or even a broad set of guidelines, they are left to invent and use their own solutions. We argue that the problem of BPM and operational BI integration is now becoming an important IS research problem. The much needed integration frameworks and systematic methodologies require the socio-technical rather than the IT perspective, creating opportunities to address the widely known problem of IS relevance, as identified by [7], [8], [9] and [10]. 4. Theoretical foundations 4.1. A holistic model of BPM From an earlier focus on technologies for BP automation and BP reengineering, BPM has evolved into a management practice that provides for governance of a business process environment towards the goal of improving agility and operational performance. BPM is a structured approach that employs methods, policies, metrics, management practices and software tools to manage and continuously optimize an organisation s activities and processes These practices incorporate myriad resources: people and the organisation, the processes themselves (considered as assets) and BPM technologies, as well as the interrelationships of the processes within the context of the business and its goals. [11]. Business leaders are increasingly adopting the so-called holistic model of BPM that encompasses four highly intertwined organisational components: strategy, people, BPs and technology [12]. While strategy defines the overall BPM-related organisational goals and directions for value creation, the actual business 3

4 value is created and delivered to customers via BPs. In general, a BP is defined as a set of coordinated activities/tasks, guided by organizational policies and procedures towards a shared business goal. BPs are supported by BPM technologies, ranging from simple BP automation to complex systems designed to provide user-driven support for ad-hoc communication, collaboration and coordination. The strategy component of the holistic model includes the enterprise-level process architecture, issues related to process-related performance measurement and BPM governance. The BP component includes methodologies for process design and ongoing improvement. The people component includes BPM related knowledge management, training and BP ownership issues. Finally, the technology component includes various BP support systems. The holistic model of BPM provides a theoretical framework that could be used by organisations to better understand the interconnected nature of different components and adopt the systems perspective when analyzing the effects of change. It could be also used to help BPM managers to identify opportunities for BPM-related business value creation and competitive differentiation The knowledge dimension of BPs The holistic BPM model has resulted in an increased recognition of the knowledge and experience people develop, use and share, while participating in all phases of the BP lifecycle. In response, BPM has started to evolve beyond transactional to include knowledge-intensive BPs. While in the case of transactional BPs their value comes from improved efficiency, it is now becoming clear that in the case of knowledgeintensive BPs, their value can be directly attributed to people s knowledge and experience required for situational decision making. This observation is very important for operational BI, as knowledge-intensive processes require different BI support than operational BPs in manufacturing organisations. We have knowledge workers who for the most part work on non-routine tasks and complex efforts. Emergent work practices are becoming common rather than prescribed projects. Most of the simple tasks have been automated or soon they will be [13]. Obviously, knowledge workers rely on highquality data from a wide variety of data sources, both internal and external and a system support that cannot be always pre-determined in advance. Therefore, knowledge-intensive processes will have different information requirements than simple transactional BPs. This section provides a brief overview of a model, previously introduced by [14] to describe a knowledge dimension of different types of BPs. This dimension will provide a critical link among BPs, types of decisions people make within these processes and their information needs, as illustrated later in the paper. Even though it is not often considered during BPM projects, knowledge is inseparable from BPs. In reality, all processes combine, to some degree, both explicit and tacit knowledge. The explicit knowledge can be written down, easily shared with other people within the same context. Examples include well structured organisational procedures. On the other hand, tacit knowledge is not documented and is very hard to externalise. Examples include knowhow, mental models and experiential insights. Externalisation of tacit knowledge and its gradual refinement result in organisational practices. They are developed over time by employees through their ability to make decisions, solve problems and critically reflect. Figure 1 depicts a theoretical framework used to describe the knowledge dimension of customerfacing BPs. Procedural BPs are highly structured and repetitive, typically found at the operational/transactional level. Technology developers often rely on standardisation and predictability of organisational procedures to design BPM solutions. This is why the existing solutions remain suitable for transactional BPs. Knowledge Explicit Procedures (speed, quantity, control) Procedural BPs (purchaseto-pay BP) Business Processes Casehandling BPs (customerfacing BP) Tacit Practices (experiential tacit) (quality, agility) Practiceoriented BPs (creative & emergent BPs) Figure 1. The knowledge dimension of BPs 4

5 On the other hand, in the practice-oriented BPs, people develop new experiential knowledge while participating in collaborative tasks and problem solving activities. The explicit knowledge comes in the form of policies that are used to help the participants to stay within the normative boundaries of their organisation as well as the wider legislative environment. In the case of practice-oriented BP the main emphasis is placed on process effectiveness, quality and creative solutions designed to meet customer needs. Finally, the case-handling BPs also combine procedures and practices. Here, the experiential knowledge comprises the practices people develop while handling various nonstandard cases of otherwise predefined BPs. It is important to note that the initial focus of BPM was on procedural BPs. However, in very recent times, while looking for opportunities for competitive differentiation, organisations are now starting to shift their focus from more-orless standard transactional BPs to the other types of BPs that cannot be easily replicated, due to the knowledge and experience of people involved Linking decisions and information The second theoretical framework used in this research has been recently introduced by Davenport [15], based on a very comprehensive study of various types of complex decisions in 26 organisations. The main objective of that study was to investigate how organisations ensure that decisions are made on the basis of the best possible information and that the right information is gathered and analysed to support decision processes. The study has resulted in a theoretical framework that identifies three different types of information environments, each characterised by a different type of relationship between information and decisions: Loosely-coupled information environments The required information is made broadly accessible to analysts and decision makers, along with the tools to analyse it. As this information is intended to inform a wide range of possible decisions, its use is based on individual initiative and not predetermined by any procedures or models. This is a typical approach used by today s BI systems regardless of the decision support needs. However, Davenport argues that in this context new approaches are required to provide much more than simply make the required information available. But at the same time, more structure or automation may not be appropriate or necessary. Structured human-decision environments In these environments decisions are still made by human professionals, but specific efforts have been made to improve decision making processes or contexts by determining the specific information and other process resources needed to make better decisions faster [15]. Compared to the loosely coupled ones, these environments have a narrower focus on particular decisions. They are designed to support decision making by, for example providing additional structure or necessary tools around decision processes. Obviously this approach is not suitable for all types of decisions and should focus only on those that are critical, due to the cost and complexity involved. Automated decision environments These environments include decision rules and algorithms embedded in the automated business processes. Decision making is delegated to the rule-engines while humans take care of exception handling. The main objective is to make the process fully automated and therefore very efficient. This only works with decisions that are well structured and reducible to a set of rules. This also means that all information needs are determined in advance so that each decision could be easily automated. Davenport argues that the above three environments should be used to guide any organisational implementation of BI applications. More precisely, in order to select the right tools for a particular type of environment, it is necessary to focus on critical decisions that need to be made but also to fully understand the relationship between these decisions and information required. Compared to Davenport's framework for linking decision and information, this paper goes one step further and aims to link processes and types of decisions made in the context of these processes and then, via these decisions, link processes with information needs. We argue that this particular link provides a starting point for further consideration of BPM and BI integration. 5. BPM and BI integration framework This section describes a theoretical framework that has been used to guide our exploratory research of non-technical aspects of BI and BPM integration, based on the above described theoretical foundations It is also informed by a very comprehensive literature review and founded in the previous BI and BPM case studies conducted by the author. 5

6 First of all, it is important to point out that the problem of BPM and BI integration could be investigated in the context of different types of BPs and across different organisational levels. This paper focuses on customer-facing BPs as they are much more complex and have a greater potential for competitive differentiation than transactional processes. In terms of their knowledge intensity, these BPs range all the way from procedural on one end of the spectrum, to practice-oriented on the other. Taking a holistic approach, we posit that different types of integration of information, decision and BPs require different type of BP improvement methodologies as well as different processes and strategies for knowledge sharing, and transfer. They, in turn, also determine the most suitable training methods for BI/BPM practitioners in this context. The main research contribution of the proposed framework is that it considers the integration problem along the BP knowledge continuum, linking information and decision with three different types of processes, thus extending Davenport s framework with the process and knowledge components. The key observation is that decisions are always made in the context of a BP, and by considering the knowledge dimension of this BP, it is possible to determine the types of decisions and decisioninformation links. In other words, it is possible to establish various patterns of relationships between processes and decisions, that, when combined with Davenport's framework, enables us to link processes and information. Furthermore, when each decision is investigated in terms of data and decision latency, it is also possible to determine the type of BI support for a particular type of BP. For example, some customer-facing processes may require a structured human-decision environment with ready-time or even real-time BI support, while others may require loosely coupled information environments and read-only BI support in the form of reports. It is important to point out that the proposed framework has been used to guide our exploratory case study research (described in the following section) and as such, it is constantly evolving. Following the recommendations made by Roseman and Vessay [10], an applicability check had been performed with the BI practitioners to confirm the relevance of the indentified problem and of the initial theoretical framework, before it was used in the case organizations. The following analysis describes the framework including the initial set of nontechnical challenges for three different types of BPs. These challenges were derived from the relevant literature and previous case studies and, as such, represent our initial understanding of these processes in terms of decisions types, information needs and knowledge required before the case studies were conducted. Procedural BPs - Decision types: By definition, procedural BPs involve highly structured decisions with predefined inputs and outcomes. In fact, the existence of structured decisions is the main reason why it is possible to model these processes in advance, with deterministic outcomes. Note that in some cases, these decisions could be fully automated, while in the others, human expertise is required to make a selection among the possible outcomes. - Process-decision-information link: When human expertise could be reduced to a set of rules, then a fully automated decision environment is highly appropriate. While this is already made possible by workflow technology, the added value of combining it with BI, enables creation of a much more comprehensive customer profile, to the extent that is not currently possible by BPM systems alone. However, when human expertise is required than the structured human-decision approach is best suited to support the data gathering and analysis phases of decision making (i.e. preparatory phases) while the fully automated decision approach is then suitable for decision execution. - Non-technical challenges of BI and BPM integration: One of the key challenges is certainly a decision-centered BP improvement methodology. This is very important, having in mind that currently available methodologies predominantly focus on control flows and models rather than decisions made. For organisations using the rule-based engines to automate decision making, ongoing management of decision rules including consistency and completeness of the rule-base also involve nontechnical challenges such as a systematic approach to rule modeling and verification as well as its governance. Lessons from KM confirm that these processes require involvement of people with domain knowledge. In addition to giving tools to domain experts so they could model their own exceptions, as with any knowledge management system it is also important provide initiatives for continuous development of new rules. 6

7 Case-handing BPs - Decision types: By definition, these processes involve semi-structured decisions and situational decision making. While in some cases, decisions involve predefined and deterministic outcomes, the challenge lies with the atypical cases where outcomes or even the processes to reach them, may not be known. This is why they are considered on the case-to-case basis with a decision maker having to interpret a particular situation and determine situationspecific information requirements to make a decision accordingly. While in the case of procedural processes, these atypical cases are treated as exceptions, in the case of casehandling BPs, situational decision make these processes knowledge-intensive. - Process-decision-information link: Irrespectively of the type of the case (typical or atypical), the structured human-decision approach is best suited to support the data gathering and analysis phases of decision making (i.e. preparatory phases). After a decision is made by the human expert, then typical cases will require fully automated decision approach, while atypical cases may require both structured human-decision approach and/or fully automated approach. On the other hand, loosely-coupled information environments, while providing a customer-facing employees with more flexibility to explore information resources in an ad-hoc way, are very likely to impact on process performance and prolong a decision making time (i.e. data latency). - Non-technical challenges of BI and BPM integration: Again, as in the case of procedural processes, design and implementation of an ongoing BP improvement methodology is probably the biggest challenge here. We argue that such a methodology should consists of a set of human-centered knowledge processes that need to be enabled and facilitated to ensure knowledge co-creation and sharing among employees and ultimately, co-evolution of practices for handling new cases with technical solutions designed to support these practices. Practice-oriented BPs - Decision types: By definition, these processes involve unstructured decisions and situational decision making processes where the decision parameters as well as its outcomes are not known in advance. This type of decisions is typically found within emergent BPs, such as for example, various design processes. - Process-decision-information link: While a loosely-coupled information environment appears to be most suitable for this type of decisions, it is important to point out that these processes are often highly collaborative in nature. Consequently, the loosely coupled environment should be extended to support collaborative decision processes. - Non-technical challenges of BI and BPM integration: If these processes are supported by loosely coupled BI solutions, any methodology for improvement of these processes needs to ensure that practices co-evolve with technical solutions. Even more, the chosen methodology also needs to evolve with the accumulated experiential knowledge. Thus, the methodology itself becomes a knowledge-intensive, practiceoriented BP at the meta level. As already pointed out, BP improvement methodologies for knowledge-intensive processes are one of many unexplored challenges of BPM [17]. The above identified types of processdecision-information links enable us to assess suitability of different BI solutions and determine requirements for different type of information environments. This is very important as loosely-coupled information environments are still the most widely used type of BI [15]. 6. Research method and findings The above described framework has been used in a series of exploratory case studies, designed to identify and analyse the BPM, BI and KM related issues across all four components of the holistic BPM model in the context of customer-facing knowledge-intensive BPs in service industries. The main objective is to identify patterns of non-technical integration, as technical patterns are already known. In line with the exploratory nature of this research, a case study method that involved an interpretative approach was adopted to capture the corresponding contextual richness and complexity [16]. The case organisations that have been involved so far come from financial, insurance and telecommunication industries. They have all reached a higher level of BI maturity and are currently using advanced BI applications in the context of customer analytics. When making the decision about suitable case organisations, we decided to focus on those with advanced BI applications used in the context of customer-facing BPs, rather than start from those currently focusing on BPM, simply because BPM support systems may or may not include BI tools. 7

8 Table 1. A holistic framework for BI and BPM integration Decision Type Decision information link Strategy (BI/BPM supported) Ongoing improvement of BI-supported BPs Integrated BPM/BI support BI/BPM training Focus Procedural BPs Case-handling BPs Practice-oriented BPs Highly structured Semi-structured Unstructured Automated decision.environment BP efficiency across segments Segment-driven BP improvement Segment driven decision and BP automation traditional skilledbased Automated and structured decision env Segment specific Value services Decision-centered knowledge processes Situated decision support Knowledge sharing strategies Loosely coupled decision environment unique products and services Collaborative knowledge sharing and co-creation Agile process support Action learning/reflective practice The suitable case study organisations were initially identified and recruited through the links established with the help of Teradata University Network. This is the largest community of BI/DW industry partners, including vendors and their customers, as well as academics (faculty staff) and their students [17]. In order to capture the accurate reflection of the issues under investigation in this context, semi-structured interviews have been conducted with the stakeholders involved in the target BPs including customer-facing employees as well as BI managers and, where existed, people in charge of these processes (process managers, BP owner). The questions asked were semistructured but retrospective in nature aiming to investigate different stages of BI/BPM integration the case organizations went through as they matured in terms of technology and their approach to customer-facing services. In addition, the current technologies used to create information environments were investigated with the help of domain experts in the context of different BP scenarios, both standard and case-based. Data collected from different sources was compared and triangulated in order to identify the main characteristics of information environments and analyse them from the KM, BI and BPM perspectives, taking a holistic approach. It is important to point out that so far, not a single organisation has been found that has fully integrated operational BI and BPM across all four components. Therefore, the framework, depicted by Table 1 represents a synthesis of issues and patterns that are expected to evolve even further, helping organizations to identify their next step. To illustrate the approach, this paper reports on a case study completed in a large financial institution located in Australia. This organisation was chosen based on their mature stage of BI implementation in the context of their customerfacing BPs, for which they have won several BI industry awards. The highlighted area of Table 1 represents the integration patterns observed in this organization, with the solid arrows indicating the progress of their BI/BPM integration journey, from procedural to case-handling BPs as well as from technical level to non-technical integration issues. Table 1 also depicts that the case organization has recognized the need for a new type of improvement methodology for their BI-supported BPs, but are yet to find and implement one. Based on data collected and analysed in this case study, this research confirmed that the introduction of operational BI, supported by an enterprise-wide data warehouse, has enabled this organisation to evolve its information environment as well as its competitive strategy, in relation to its customer-facing processes. For example, their initial focus was on implementation of an automated decision environment. This environment included a very sophisticated BI analytics tool, used for identification of different categories of their customers. Then a rule-based application was used to automate pre-defined decisions and their execution. Therefore, the initial implementation of the automated information environment has enabled this organisation to compete on the basis of the procedural BP, with different process instances offered to different types of customers. Compared to the traditional workflow-based BPM solutions that have been widely used by the financial industry over more than a decade, this type of BI and BPM integration 8

9 in the context of procedural BPs has created new opportunities for competitive differentiation, not possible if workflows are implemented alone. This observation confirms the point made by Watson that the importance of BI technology for competing in the market place is greater for high volume-operations [18]. However, as similar advanced technical solutions are now being implemented across the whole industry consequently, the information environment of this company continues to evolve from the automated decision to a structured human-decision environment, even for the standard processes. They are now aiming to inject more human knowledge and expertise into their customer-facing BPs. Employees are already in a position to combine their own understanding of customer-needs obtained through personal interaction with them. Therefore, this particular pattern of BI and BPM integration at the technical level is already well known among the leaders in BI, in particular those in the area of Active enterprise intelligence and customer analytics. In terms of Davenport s information environments, this organisation is gradually moving from the fully automated to the structured human-decision environment. Therefore, from the knowledge and BPM perspectives, this organisation is moving along the knowledge continuum from the procedural to case-handling processes ( value-adding services ). However, this move is not driven by exceptions or efficiency but an opportunity to add-value to their processes. This change is very much caused by their need to create new opportunities for competitive differentiation in a fiercely competitive industry where they cannot compete on the basis of their products alone. Therefore, the increased focus on the structured human-decision environment has enabled them to compete on the basis of their customer-facing processes with value-add provided by their knowledgeable employees. However, it is also important to point out that not all procedural BP could be and should be turned into case-handling BPs. This decision is largely based on the customer s current value and their future potential to bring value. This case study also confirmed that this organisation is interested to move even further along the knowledge continuum, even towards practice-oriented processes. However, they also confirmed that possible technical solutions that would enable flexible implementation of a loosely coupled information environment have not reached the required maturity. While the need for BI and BPM integration at the strategy level was not initially considered when this organisation started to use their customer analytics solutions, a possibility to add more value to their processes has gradually extended their initial BI strategy to take an advantage of BPMrelated value-add and process thinking, even though they are not using the term BPM. They are now competing on the basis of value-add services, that are in essence processes. The move towards strategy level integration was also evident in very recent times when this case organisation faced the need to integrate their, up-to-now, independent functional data warehouses. This is typically considered to be a BI problem, related to enterprise-level data integration. However, this organisation is now starting to consider cross-functional BPs, in order to better understand a context for the enterprisewide data integration and thus, determine how the integrated data may be used. The elements of BPM have also been observed in relation to the people component, in particular training of customer-facing employees. So far the main focus of their training has been on BI tools. However, they have already recognized the need to adopt the process view to analyse their processes. But, instead of using the control-flow-based models and the associated methodologies as it is typically done in BPM, they aim to focus on decisions made within these processes. These decisions are the touch-points where they can create value. They have also implemented a number of human-centered knowledge sharing strategies among customerfacing employees. They are now interested to explore opportunities created by collaborative technologies including wiki-based solutions to better facilitate their knowledge sharing. Looking from the BPM perspective, this example confirms the point made by Davenport [19] that BPM requires new methods for continuous improvement of decision-centered BPs. Thanks to BI solutions, these BPs are now becoming more knowledge intensive rather than highly routine, enabling companies to compete on analytics [20] but in the context of their processes. Finally, this case also confirmed the previous point that organisations do lack systematic methodologies for BP improvement of decisionintensive processes supported by BI. However, further data collection and analysis is required in order to further investigate this problem. 9

10 7. Conclusions and future work While the issue of BPM and BI integration is becoming more and more important, especially with the very recent raise of operational BI, current integration efforts remain mostly at the level of technology. In fact, the technical integration is no longer considered to be an issue. As technical solutions are now widely available, the focus is shifting towards nontechnical issues as the next frontier of BI/BPM integration. This paper adopts a holistic BPM view to investigate patterns of integration across strategy, processes, people and technology components. By combining the outcomes of ongoing multi-site exploratory case studies, this research aims to create an evolving map of integration issues and patterns to guide organisations in their integration efforts, while making research contribution to both BPM and operational BI fields. Our current and future work involves more exploratory case studies in different service organisations in the context of their customer-facing knowledge intensive processes, in particular practice-oriented processes and opportunities for BI applications in this context. 8. References [1] Indart, B. (2006), Operationalizing Business Intelligence Turning Insight Into Action, Business Intelligence Journal, Second Quarter, 11, 2 pg. 35. [2] Cunningham, D. (2005), Aligning Business Intelligence with Business Processes, TDWI Research, Vol. 20, November [3] Williams S. and Williams N. (2003): The Business Value of Business Intelligence, Business Intelligence Journal, Fall 2003, pp [4] Imhoff, C. (2005), Streaming Processes for Front- Line Workers: Adding Business Intelligence for Operations, Operational Business Intelligence White Paper, Intelligent Solutions Inc., December [5] Grigory D., et al. (2004), Business Process Intelligence, Computers in Industry, Elsevier, 53, pp [7] Benbast I. And Zmud, R.W. (1999), Empirical Research in Information Systems: The Practice of Relevance, MIS Quarterly (23:1), pp [8] Davenport, T.H. and Markus, L.M. (1999), Rigor and Relevance Revisited: Response to Benbasat and Zmud, MIS Quarterly (23:1), pp [9] Baskerville, R. And Myers, M.D. (2004), Special Issue on Action Research in Information Systems: Making IS Research Relevant to Practice, Foreword, MIS Quarterly (28:3), pp [10] Rosemann, M. And Vessey, I. (2008), Toward Improving the Relevance of Information Systems Research to Practice: The Role of Applicability Checks, MIS Quarterly (32: 1), pp [11] Gartner (2008a): Hype Cycle for Business Process Management, July 2008, Gartner Research, Report No. G [12] Harmon, P. (2007): Business Process Change, Second Edition, Morgan Kaufmann. [13] Desouza K. (2007): (ed), Agile Info. Systems, Elsevier. [14] Marjanovic, O. (2007) The Next Stage of Operational Business Intelligence: Creating New Challenges for Business Process Management Proc. of HICSS-40: The 40 th Hawaii International Conference on System Sciences, Hawaii, 4-6 January 2007, IEEE [15] Davenport, T. (2008): Linking Decisions and Information for Organisational Performance, A Client Study, October [16] Yin, R. (2003), Case Study Research: Design and Methods, 3rd ed, CA: Sage Publications. [17] Teradata University Network (last accessed in June 2009) [18] Watson, H. (2008): Why Some Firms' BI Efforts Lag, Business Intelligence Journal, Vol 13, No 3. [19] Davenport, T.(2005): Thinking for a Living, Harvard Business School Press. [20] Davenport, T. And Harris, J. (2007): Competing on Analytics: The New Science of Winning, Harvard Business School Press, [6] Gaaloul,W. (2005): Business Process Intelligence: Discovering and improving transactional behavior of composite services from logs, Proc. of the First Int.. Conference on Interoperability of Enterprise Software and Applications, Geneva, Switzerland, Feb. 10