Business intelligence as an enabler of organizational agility

Business intelligence as an enabler of organizational agility Jean-Pierre Kuilboer, Hanne Russ, Noushin Ashrafi University of Massachusetts Boston, Boston, United States E-mail: Jeanpierre.kuilboer@umb.edu Abstract In a competitive business world, the ability to detect and deal with change is a requirement for survival. Agility and business intelligence are instrumental to understanding the intricacies of market changes and facilitating the delivery of a faster and better response. We focus on these two phenomena and argue that while organizational agility is critical for survival in the current volatile business environment, business Intelligence solutions have the potential to be enablers for achieving agility. We establish a link between business intelligence and agility and show how business intelligence capabilities can help achieve agility at operational, portfolio, and strategic levels. Keywords: Business Intelligence, Agility Introduction Business environment is experiencing an unprecedented volatility and doing business in this environment is becoming increasingly challenging. Markets, competition, customer demands, and technology are changing at a rapid pace. Niche markets grow because customers seek customization and switching costs are low. Innovation is happening at an accelerating rate as product lifecycles decrease. Fast changing markets, pressure from increasing costs, international competitiveness, Internet usage and a short development time for new products all contribute to uncertainty and intense competition (Tseng et al, 2011). Organizations strive for gaining better, faster, and more complete insight into ever changing market demands and applying that insight to understanding the changing environment. PricewaterhouseCoopers called the period from 1996 to 2006 10 years of high-speed change characterized by unsettling twists and turns (Sull, 2009). In these unpredictable and unstable times, companies need certain capabilities for sustainability and survival. They need foresight and responsiveness. Business agility is a relatively new paradigm considered as a solution formaintaining competitive advantage during times of uncertainty and turbulence in the business environment (Mathiassen et al., 2006). To achieve agility, organizations need to be able to sense and respond to predictable and unpredictable events. Thus, agility requires organizations to build up economies of scope in order to effectively respond to changing environment and to be productive at the same time (Melarkode et al. 2004; Horney et al. 2010). Executives have already recognized the importance of agility to business success and are pursuing instruments to implement the concept. One instrument that has a high potential of becoming the major enabler of agility in organizations is business intelligence. Fast analysis, rapid deployment, and real-time monitoring of events via portals and dashboards based on trusted, accurate information are features of holistic BI solutions that could make agility achievable (Henschen, 2010; Melarkode et al. 2004; Mohanty, 2008; Sull, 2009). 1

Business intelligence (BI) refers to the organizational ability to capture internal and external information and convert them into knowledge. The assimilated knowledge is then used to develop a mechanism towards achieving faster and better responses to change. BI is indeed transforming decision making and information technology across all industries. This is largely due to the everincreasing availability of data. The explosive volumes of data are available in both structured and unstructured formats. They are analyzed and processed to become information within some context hence providing relevance, and purpose to the decision making process (Sabherwal et al., 2011). BI enables decision makers to optimize business resources, increase efficiency, reach goals, and identify areas for growth. Both agility and BI concepts have received a great deal of attention from scholars and practitioners (Baars et al., 2008; Burgess, 1994; Chaudhury et al., 2011; Dove, 2005; Meyer, 2001; Narasimha et al., 2006). A great deal of work has been done to address the role of IT to achieve agility (Bharadwaj, 2005; Chen et al., 2011; Fink et al., 2007; Lee et al. 2006; Lu. et al., 2011; Overby et al., 2006; Sambamurthy et al., 2003; van Oosterhout et al., 2006; Weill et al., 2002). The impact of agility on BI has been discussed in one article (Zimmer, 2012). However, to our knowledge, using business intelligence as a facilitator to achieve agility has drawn little attention; Chen et al. have touched upon the impact of BI on organizational performance. Interestingly, despite little attention to role of BI to gain business agility, there is plenty of evidence in published work indicating that business intelligence has the potential to improve organizational performance. Some Researchers have asserted that a knowledge-driven enterprise can enhance agility (Goldman et al., 1995; Harrigan et al., 1991; Mirca etal., 2011;Mohanty, 2008). Others believe that accessibility of information, data-based decision making and enterprise-wide information sharing are key factors to provide early insight to business opportunities and disruptions (Baars et al., 2008; Bharadwaj et al. 2005; Chen at al., 2011). Fast analysis and rapid deployment are mentioned to advance agility as well (Elbashir et al. 2008; Henschen, 2010; Lu et al., 2011; Mathiassen et al., 2011). Melarkode et al. report that technologies making agility more attainable include real-time monitoring of events via portals and dashboards, and anytime, anywhere access to applications and data (Melarkode et al., 2004). Mohanty(2008) asserts that the major difference between agile organizations and others is the ability to leverage the data they have amassed to make informed decisions by delivering the right information to the right people at the right time (Mohanty, 2008). As mentioned earlier many researchers indicate that IT capability positively relates to agility (Lu et al., 2011; Melarkode et al. 2004; Mohanty, 2008; Sull, 2009; Tseng et al. 2011). All of these enablers have characteristics of BI solutions, but a clear link between business intelligence and agility has not been established and a strong argument justifying investment in BI in order to realize agility has not been made. In this paper we focus on these two fairly new, but exceedingly important phenomena in modern business world; agility and business intelligence. We emphasize the critical role of agility for survival and gaining competitive advantage in the current volatile business environment and argue that business intelligence solutions have the potential to be an enabler and a catalyst for achieving agility. We show that the effective use of BI solutions, capabilities, and tools could achieve desired agility by sensing changing business needs and responding to them in a timely fashion. We have built upon existing research that identifies three levels of agility (Sull, 2009) and have shown how business intelligence capabilities can help achieve agility at operational, portfolio, and strategic levels. By establishing a clear relation between business intelligence and agility we hope to help justify investing in business intelligence solutions, which requires substantial upfront outlay. This should be helpful to the management looking to taking advantages of many benefits of business agility. The 2

organization of the paper is as follows. The next two sections describe the two concepts of agility and business intelligence followed by demonstrating how to use business intelligence methodically towards an agile organization, where agility is woven into all facets of the organization. We then conclude by summarizing our arguments and citing the limitations of the application of BI. Organizational agility Organizational or business agility is the capacity to detect and seize opportunities faster than the competition. It is also about anticipating events and changes and to respond to those new conditions appropriately. An agile organization is capable of responding to changes quickly, is resourceful, and is able to adapt to the changing environment (Mathiassen et al. 2006). Quickness here refers to the speed for the organization to react to change. It is the time it takes to sense trends and events, to understand them, to evaluate the effects for the business, to determine options and the course of action, and to carry out the response, which decided upon. For an organization to be resourceful means to have the people, technology, processes, and know-how in place to effectively respond. Adaptability requires the ability to learn as well as having flexible processes and products (Mathiassen et al. 2006). Sull (2009) identifies three different types of agility: Operational agility, Portfolio agility, and Strategic agility. Operational agility Operational agility refers to the company s ability to realize changes to improve internal operations and processes by reducing cost, improving quality improvements, and refining distribution processes. Organizations with the ability to seize these internal improvement opportunities can be as successful as organizations that mainly rely on introducing new products or services. Examples of companies that possess operational agility and have been successful are Toyota, FedEx, and Southwest Airlines (Mathiassen et al., 2006). The success of operational agility depends upon a number of factors including ability to access and analysis internal data on-demand. Sull (2009) indicates the need for Shared real-time market data that is detailed and reliable. He further suggests the needs for staying inflow of information and maintaining focus on critical objectives. Portfolio agility Portfolio agility focuses more on recognizing and realizing new business opportunities with existing resources, such as cash, talent, and managerial attention. The goal is to reallocate resources from units with stagnating business to units that have growth potential. A study by McKinsey suggests that this kind of agility fosters revenue growth. This can be very challenging to achieve because it can disrupt the power balance within an organization. Therefore, top executives need enough control over resources to achieve portfolio agility. In addition, the organization needs to have a pool of versatile managers that can be deployed across different units. The realization of portfolio agility also depends on information readily available and the capability for fast and accurate analysis of internal and external data and information. Sull (2009) emphasizes the need for making rational decisions based on facts rather than other criteria such as emotions and politics. Strategic agility Strategic agility refers to the ability to detect and decisively seize a golden opportunity; the game changers. Strategic agility often requires rapidly scaling up a new business, aggressively entering a new market, betting heavily on a new technology, or making significant investments in capacity (Sull, 3

2009). According to Tseng & Lin (2011) embracing agile strategies benefits companies in many ways such as: Quick and efficient reaction to changing market requests, Capability to customize products and services delivered to customers, Capability to produce and deliver new products in a cost-efficient manner, Decreased manufacturing costs, Increased customer satisfaction, Removal of non-value-added activities, and In order to reap these benefits organizations have to build up responsiveness, adaptability, and speed. Furthermore, businesses constantly encounter small opportunities and act upon them to stay competitive, but once in a while come along a golden opportunity that can generate considerable pay off. To catch that moment requires awareness and acting quickly to grab the opportunity. Capturing structured and unstructured data including social media buzz could be a tremendous help to develop the necessary awareness. Business intelligence Business intelligence (BI) is defined as providing decision makers with valuable information and knowledge by leveraging a variety of sources of data as well as structured and unstructured information (Sabherwal, 2011). According to this definition, the primary goal of business intelligence is to support decision making based on hard facts. These hard facts are extracted from various sources and refer to structured and unstructured data and information. Data entails raw facts, observations, or perceptions lacking context that are commonly generated by business events; transactions with or within the organization. It is the input for data warehouses or similar repositories. Information is data with context and meaning that can be input as well as the result of a business intelligence application. Based on data and information, knowledge is created as justified believes about relationships among concepts relevant to that particular area, which can be acted upon (Mohanty, 2008; Sabherwal et al. 2011). The goal of BI is to collect vast amount of data from various sources and turn them into information and knowledge, and eventually into actionable insights. A holistic Business intelligence comprised of business intelligence solutions that contain business intelligence capabilities supported by BI tools. A holistic BI solution should incorporate the following capabilities: Organizational Memory, information Integration, insight Creation, and presentation. Those capabilities can be seen as steps that in combination can provide information about the market, identify opportunities, or attain growth through partnerships. Each step depends on the preceding one (Sabherwal et al., 2011). Organizational memory The first capability is organizational memory that lays the foundation for the BI solution. It is the storage of information and knowledge that the organization has collected in the past. One of the most common tools for this capability is a data warehouse. Before the data in this repository can be utilized, it has to be extracted from its original source, transformed, and loaded into the warehouse. Another tool that serves as a repository for unstructured textual data is a document management system. 4

Information integration The second capability is information integration that assimilates and links structured and unstructured data from a variety of sources, such as internal databases and knowledge repositories. Tools that integrate unstructured data are text mining and web mining. Both of these tools atomically analyze large volumes of textual data and extract relevant information from it. They significantly reduce the time it would take a human to catalogue these data. Insight creation The third capability is insight creation that enables the organization to understand past events and make predictions about the future. Data mining tools provide in-depth analysis of data with the purpose of building predictive models and answering questions. Web analytics, on the other hand, examine how users interact and navigate on a company s website with the help of click stream data (Chaudhuri et al., 2011). Presentation capability The last capability is presentation capability that displays these insights in different ways to make them easy to grasp and to utilize. Online Analytical Processing, for example, supports multidimensional data views and allows users to aggregate, filter, drill down, and pivot the data. Dashboards allow users to customize the information they would like to monitor and facilitate display (Chaudhuri et al., 2011). According to Sabherwal& Becerra-Fernandez, these four Bi capabilities are distinct and at the same time they are mutually synergistic in nature. They provide inputs to each other; information from the past becomes an input for information integration, which in turn produces synthesized information based on structured, unstructured as well as internal and external information that can be used as the basis for insight creation. Presentation capability then assimilates this insight and makes them available to relevant users. Table 1 summarizes technologies that enable the four capabilities. Capability Organizational Memory Information Integration Insight Creation Presentation Table 1 Technologies enabling BI capabilities Technologies Data Warehousing, Enterprise Resource Planning, Knowledge Repositories, Digital Content Management Systems, Document Management Systems Environmental Scanning, Text Mining, Web Mining, Radio Frequency Identification Devices Data Mining, Business Analytics, Real-Time Decision Support Online Analytical Processing (OLAP), Visualization, Digital Dashboards, Scorecards, Business Performance Management The effectiveness of these capabilities relies on the investment on relevant technologies. Since the four capacity work together to produce the benefits of BI, itis essential to attain technology supporting each capability, hence the question of upfront investment in tools. The investment could be justified summing up the benefits of BI as an enabler to achieve agility. All of these capabilities provide an organization with the opportunity to sense trends and upcoming 5

changes in its environment. Web Mining, data mining, and dashboards allow the business to look into its own data and external information and to monitor them. This enables the detection of unusual developments. Data Warehousing, RFID technology, real-time decision support and visualization grant an organization the ability to respond to these changes in a timely and informed manner. Therefore, the four capabilities of BI solutions complement each other and provide an organization with the ability to sense and respond quickly. In what follows we explain specifically the benefits of BI as an enabler for agility. BI as an enabler for agility In order for business intelligence to be an enabler for organizational agility, it has to help build attributes necessary for agility in general, namely responsiveness, adaptability, and speed. It also has to enable organizations to achieve the three particular types of agility: operational, portfolio, and strategic agility. Enabling operational agility Organizations possessing operational agility are able to benefit from improving their internal processes and operations. The organizational memory capability of a BI solution captures most data within an organization that can be processed. This can also include the documentation of internal processes. With the help of text mining, users are able to compare processes across the enterprise and detect differences. Based on performance data, managers can then assess which of the process versions is the most efficient or effective. This can lead to process refinements through implementing a best practice process. For example, if the budgeting process of a specific finance team yields very accurate result, it should also be implemented in other relevant finance teams. Another area of BI enabling operational agility is the monitoring of key performance indicators with dashboards or scorecards. BI tools cannot perform operational improvements, but they can initiate the effort by pointing out deviations and tracking developments. If a business unit continually exceeds a threshold, it might be a sign that this unit is experiencing problems. On the contrary, a unit that is outperforming a certain target value might have made some adjustments that can be repeated and extended in the future. BI is also a good instrument for experimenting with internal adjustments. Through real-time data and analytical functions, it can quickly capture and illustrate results (Horney et al., 2010). In addition, BI also helps businesses take advantage of synergies with technologies, such as RFID technologies. Costs can be reduced if distribution is shared and goods can be tracked and redirected as needed. The decisive factor in achieving portfolio agility is to distinguish stagnating business units from units with growth opportunities. Enterprise resource systems and other data repositories hold current and historical data which can be used to visualize trends. These can illustrate the R&D activity of a segment, its sales numbers, its costs and other factors over time. Declining R&D activity and sales paired with increasing costs can indicate a declining segment. BI tools can also perform macro data collection and analysis with environmental scanning. Results can indicate shifts in the industry or the emergence of new standards in terms of technology or regulations. This can identify segments that might become obsolete or rather gain more importance in the future. Furthermore, external market data combined with internal customer information can be analyzed with data mining techniques. This can reveal unforeseen patterns, such as new 6

preferences or tastes. If the company has the ability to meet those new demands, it can then invest more funds, talent and attention into those segments. Since talent is also one of the major resources that need to be reallocated in the process, organizations should take advantage of BI tools to find the right people within the organization for taking on new positions. An option would be to create a talent database for general managers that records attributes such as experience, qualifications, track record, networks, and location (Horney et al., 2010). Business intelligence can neither overcome political obstacles nor ensure central control over resources. However, it can provide decision makers with the information and insights supporting the most promising course of action. It adds credibility to decision makers that might help them to get buy-in from relevant stakeholders within the organization. Enabling strategic agility Strategic agility is the ability to seize that rare game changing opportunity by reacting quickly. In order to achieve this type of agility, organizations need to have networks with suppliers in place that provide them with the necessary flexibility. However, the risk of failure is high since large initial investments need to be made. Therefore, the organization has to be certain of the potential of the opportunity. BI can provide organizations with this kind of insight. Due to visualization capabilities, executives are able to assess the firm s financial situation and other resources at one glance. The information is timely and reliable. Thus, they can make their decisions based on the most relevant facts. In addition, the organization needs relevant evidence to get buy-in from its suppliers. BI also provides information sharing and exchange. This enables a firm to share insights with external parties, such as suppliers, in order to make collaborative decisions. It can also be utilized to quickly share information within the own organization in order to speed up the response. Agility stakeholders Agility depends on the relationship between the company and relevant stakeholders. In order to achieve the capability to respond and adapt quickly, an organization has to account for suppliers and customers. As mentioned, suppliers are critical for seizing golden opportunities quickly. To ensure their support, the company has to supply them with relevant and timely information about anticipated changes. Customers play an essential role as well. They expect that their new demands and preferences are met fast. Thus, the company has to interact with them to receive relevant information and feedback on its portfolio and strategy. BI is instrumental in expediting the channel of communication between the business and its suppliers as well as its customers. Figure 1 illustrates the need for an agile interaction between business and its suppliers and customers. 7

Figure 1 Agility Stakeholders Business intelligence solutions are able to incorporate these stakeholders inputs into organizational decision making. The organization can explore and discuss scenarios with its suppliers by deploying environmental scanning, what-if analysis, and predictive analytics. Through visualization, results can be easily shared and understood. The company can also analyze customer data that it collects at point-of-sales or through direct contact with customers. Information on individual customers can indicate particular preferences or habits. In response to that, the company can customize its offerings. In addition, technologies such as data mining can support a company in anticipating demand. Therefore, by recognizing trends and changes early on new demands and preferences can be satisfied quickly, if the firm chooses to take the opportunity. Conclusion Drawing a conclusion from the analysis, business intelligence has high potential of being an enabler of organizational agility. It enhances the speed of reaction by providing real-time information, visualization, and flexible analysis capabilities. Furthermore, BI increases responsiveness through offering tools that help organizations to anticipate trends and changes and by empowering users. BI also augments adaptability by providing reliable and actionable insights. However, BI does not guarantee improved agility. The business intelligence solution has to be aligned with the organization s goals and has to be deployed properly. In addition, the structure of the organization needs to allow data-driven decision making. Otherwise, the results extracted from BI tools will not make a difference and the organization will resist the suggested course of action. Also, an overreliance on BI tools might reinforce searching for opportunities and developments only in current domains. Managers might ignore signals in new domains and their decision might be misdirected. Nonetheless, BI grants better insights in internal strengths and opportunities (Lu et al., 2011). Besides strengthening its capabilities with BI, an organization also needs to develop other capabilities such as supplier networks, liquidity, and talent in order to achieve agility. BI can support those efforts but it cannot substitute them. Therefore, it is a catalyst and enabler for agility in a sense that it facilitates detecting opportunities and risks, and managing strengths and weaknesses. 8

References Baars, H. and Kemper, H-G. (2008), Management support with structured and unstructured data Anintegrated business intelligence framework, Information Systems Management, Vol. 25, No. 2, pp.132 148. Bharadwaj, A., and Sambamurthy, V. (2005) "Enterprise agility and information technology management: The CIO's manifesto," SIM Advanced Practices Council Publication, 2005. Burgess, T.F. (1994), "Making the leap to agility: Defining and achieving agile manufacturing through business process redesign and business network redesign," International Journal of Operations & Production Management, Vol. 14, No. 11, pp. 23-34. Chaudhuri, S.Dayal, U. and Narasayya, V. (2011) An overview of business intelligence technology, Communications of the ACM, Vol. 54, No. 8, pp. 88-98. Chen, X. and K. Siau, (2011) Impact of business intelligence and IT infrastructure flexibility on competitive performance: An organizational agility perspective, Thirty Second International Conference on Information Systems, Shanghai 2011, pp. 1-11. Dove, R. (2005) "Fundamental principles for agile systems engineering," Conference on Systems Engineering Research, Hoboken, NJ, 2005. Elbashir, M.Z., Collier, P.A. and Davern, M.J. (2008), Measuring the effects of business intelligence systems: The relationship between business process and organizational performance, International Journal of Accounting Information Systems, Vol. 9, No. 3, pp. 135 153. Goldman, S.L., Nagel, R.N. andpreiss, K. (1995),Agile Competitors and Virtual Organizations, Van Nostrand Reinhold, New York. Harrigan, K.R., and G. Dalmia, G. (1991) "Knowledge workers: The last bastion of competitive advantage," Planning Review, Vol. 19, No. 6, pp. 4-7. Henschen, D. (2010), Foundation for BI, InformationWeek, Dec. 21, 2010, pp. 16-27. Horney, N., Pasmore, B. and O'Shea, T. (2010), Leadership agility: A business imperative for a VUCA World, People&Strategy,Vol. 33, No. 4, p. 34. Lee, O-K. D. Banerjee, P., Lim, K.H., Kumar, K., van Hillegersberg, J., and Wei, K.K. (2006), "Aligning IT Components to Achieve Agility in Globally Distributed System Development," Communications of the ACM, Vol. 49, No. 10, pp. 48-54. Lee, O-K.Lim, K.H. Sambamurthy, V. and Wei, K.K. (2007), "IT-Enabled Organizational Agility and Firms' Sustainable Competitive Advantage," the Twenty-Eighth InternationalConference on Information Systems, Montreal, Canada, 2007. Lu, Y. Ramamurthy, K. (2011). Understanding the link between information technology capability and organizational agility: An empirical examination, MIS Quarterly, Vol. 35, No. 4, pp. 931-954. Mathiassen, L. and Pries-Heje, J. (2006), Business agility and diffusion of information technology, European Journal of Information Systems, Vol. 15, No. 2, pp. 116 119. Melarkode, A. From-Poulsen, M. and Warnakulasuriya, S. (2004), Delivering agility through IT, Business Strategy Review, Vol. 15, No. 3, pp. 45-50. Meyer, C.(2001), "The second generation of speed," Harvard Business Review, Vol. 79, No. 4, pp. 24-26. Mircea, M. Ghilic-Micu, B. and Stoica, M. (2011), Combining business intelligence with cloud computing to delivery agility in actual economy. The Bucharest Academy of Economic Studies, 2011.Retrieved 15 April 2012 from http://www.ecocyb.ase.ro/12011%20pdf/marian%20stoica.pdf. Mohanty, S. (2008), Measuring the value of intelligence in business intelligence, DM Review, Nov. 6, 2008, pp. 21-23. Narasimhan, R. Swink, M. and Kim, S.W. (2006), "Disentangling leanness and agility: An empirical investigation," Journal of Operations Management, Vol. 24, No. 5, pp. 440 457. Neumann, S. and Fink, L. (2007), "Gaining agility through IT personnel capabilities: The mediating role of IT infrastructure capabilities," Journal of the Association for Information Systems, Vol. 8. No. 8, pp. 440-462. Overby, E. Bharadwaj, A. and Sambamurthy, V. (2006), "Enterprise agility and the enabling role of information technology," European Journal of Information Systems, Vol. 15, No. 2, pp. 120-131. 9

Raber, D. Winter, R. and Wortmann, F. (2012), Using quantitative analyses to construct a capability maturity model for business intelligence, 45th Hawaii International Conference on System Sciences, Jan. 4-7, 2012, pp. 4220-4228. Sabherwal, R., and Becerra-Fernandez, I. (2011), Business Intelligence: Practices, Technologies, and Management, John Wiley & Sons Inc., Hoboken, NJ. Sambamurthy, V., Bharadwaj, A. and Grover, V. (2003)"Shaping agility through digital options: reconceptualizing the role of information technology in contemporary firms," MIS Quarterly, Vol. 27, No. 2, pp. 237-263. Sull, D. (2009), Competing through organizational agility, McKinsey Quarterly, Dec. 2009. Sull, D.(2009), How to thrive in turbulent markets, Harvard Business Review, Vol. 77, No. 1, pp.78-88. Tseng, Y-H.and C-T Lin, C-T. (2011), Enhancing enterprise agility by deploying agile drivers, capabilities and providers, Information Sciences, Vol. 181, No. 17, pp. 3693 3708. vanoosterhout, M., Waarts, E. and van Hillegersberg, J. (2006), "Change factors requiring agility and implications for IT," European Journal of Information Systems, Vol. 15, No. 2, pp. 132-145. Weill, P. Subramani, M. and Broadbent, M. (2002), "Building IT infrastructure for strategic agility," MIT Sloan Management Review, Vol. 44, No.1, pp. 57-65. Zimmer, M., Baars, H. and Kemper, H.G. (2012), The impact of agility requirements on business intelligence architectures, 45th Hawaii International Conference on System Sciences, Jan. 4-7, 2012, pp. 4189-4198 10