Chapter 15

206

C h a p t e r

15 Building Business Intelligence

It goes without saying that every business wants to be intelligent in its strategies and actions and every business manager wants to make intelligent decisions. The question is therefore, how does a business or a manager become “more intelligent”? Clearly, smart people, with lots of graduate degrees, good instincts, talents, and a little bit of luck are going to be well on their way as individuals and their decisions should benefit the organization, but is there a way to make everyone more intelligent? Are there practices, methods, techniques, or processes that could raise the level of decision- making performance of the whole organization such that it becomes more than the sum of its parts?

While in principle IT has long been considered a key way to achieve business intelligence (BI)—remember group support systems, decision support systems, expert systems or knowledge management systems—in practice, few companies have significant business intelligence capability in their IT organizations, nor do they have plans to develop one (Bitterer 2010; Davenport 2007). Many reasons for this exist including a lack of data standards and definitions, inadequate processing and analytic power, poor data governance, and low priority among business executives. Today, however, the situation is beginning to change. First, the business world has become more complex and competitive and managers are looking for better ways to understand their changing marketplace. Second, the Internet and the enhanced con- nectivity it enables through Web sites, mobile computing, and social networking, is generating huge amounts of data that have the potential to inform the organization about its products, services and customers, and identify new and lucrative business opportunities. Third, technology is finally catching up with the need. Data storage has become cheaper; new analytic tools are available; and extra processing power is available as needed through the cloud. Thus, many IT organizations are concluding that it is time to look more seriously at business intelligence and how IT can effec- tively enable it.

This chapter explores how IT can help make business intelligence a reality. It first examines the nature of business intelligence, where it fits with other internal and exter- nal forms of data, information and knowledge, and how it is evolving in organizations.

Chapter 15 • Building Business Intelligence 207

Next, it explores the demand for BI in organizations, what is driving it, and the value organizations are seeking from it. Some of the obstacles to effective BI are then described, as well as the role of IT in delivering BI. Finally, it concludes with ways managers can improve BI in their organizations.

Understanding BUsiness intelligence

The first challenge when writing about BI is clarifying what is meant by this term. For some, it appears to be another level in the data–information–knowledge–intelligence con- tinuum, whereby data are collected, organized, connected with other data, analyzed, and presented in a format that can be used to make decisions (Chowdhury 2011). For others, it is characterized by the use of analytics to make better decisions, optimize a distinctive capability or external relationship, or to provide customers with a new or augmented product or service (Davenport 2013; Davenport and Harris 2007). Still others see BI as different from analytics, focusing on integrating data from multiple internal and external sources to provide historical, current, and predictive views of business operations (Shen 2011). Finally, BI has been portrayed as a set of information manipulation practices, such as query, mining, reporting, and interactivity that is linked to but separate from informa- tion management practices (including master data management, information architec- ture, data quality, data administration, and data integration) (Bitterer 2010).

The members of the focus group did not spend time discussing an exact def- inition of BI. Instead, they saw the term as referring to “an evolving ecosystem around our data vision” or “an electronic nervous system.” They viewed BI as an organizational capability that could be used to bring the right data, information, knowl- edge, and intelligence to bear on a business problem, opportunity, or decision. This capability builds on a strong foundation of good quality internal data, effective infor- mation management practices, and a comprehensive and holistic knowledge of the business and marries these to a variety of new and older types of internal and external data and new practices for understanding, manipulating, and presenting data. Focus group members stressed that it is the combination of data, practices, and knowledge that creates good BI.

Their organizations all recognize that the nature of the data they use is changing and becoming more complex. While traditionally their BI functions have focused on historical reporting, BI is now morphing to enable more real time and predictive views of business operations. The consensus of the group could be summarized as follows:

Our BI activities should help us develop the capability to

• Anticipate the future instead of reacting to the past; • Empower employees’ memory, insight, and reach and give them the authority to decide

and act; • Sense what is happening in the organization’s environment through gathering and

using both internal and external structured and unstructured information; • Connect internal and external functions and resources across geographies to accom-

plish desired business outcomes; • Question the status quo and create new opportunities; • Focus on only the most relevant information to support timely decisions/actions

closer to the point of impact and consequence.

208 Section III • IT-Enabled Innovation

The focus group concluded that effective BI initiatives start with a cultural “infor- mation orientation” that percolates through all organizational activities to develop mechanisms to support processes and decisions with information; capabilities to dis- cover new patterns, associations, and relationships among data; a flexible technical infrastructure that incorporates new types of data and their governance into work for added value; tools to exploit data more effectively; and the knowledge and skills to do so at all levels of the organization. Figure 15.1 illustrates the many components of this BI ecosystem.

the need for BUsiness intelligence

The need for good intelligence about a business, its customers, and its operations is not new. In the 1990s, many companies jumped on the knowledge management bandwagon seeking to build a knowledge-creating company and to use knowledge for strategic advantage (Davenport and Prusak 1998; Hatten and Rosenthal 2001; Stewart 1997). Similarly, the need for improved information to support decision making is something that has been revisited about every six or seven years over the past three decades, using slightly different names, such as decision support systems, executive support sys- tems, online analytical processing (OLAP), and competitive analytics (Davenport 2013; Davenport and Harris 2007).

What is new is the recognition within IT, if not the rest of the organization, that BI is a top priority for new IT development (Davenport and Harris 2007; Hostmann et al. 2009). For CIOs, there are two major reasons for this new interest:

Data Information

Management Intelligence

Creation

• Reports

• Dashboards

• Data mining

• Information- enhanced processes

• Queries

• Graphics and visualization

• Real-time analysis

• Historical, current, and predictive analysis

• Information- enhanced products and services

• IM strategy and principles

• Enterprise information- architecture

• Metadata

• Data management

• Data integration

• Data quality

• Data administration

• Transaction data

• Internal structured data

• Internal unstructured data

• External structured data

• Master data

• External unstructured data

• Real time data

figUre 15.1 The BI Ecosystem

Chapter 15 • Building Business Intelligence 209

1. The explosion of data. It is well documented that both the amount and type of data are increasing exponentially and this is creating both headaches and opportunities for the IT function (Hopkins et al. 2010; Shen 2011). Combined with lower storage costs and increased processing power, companies are now able to capture, store, and analyze a much wider variety of data than in the past. Chief among these are a wide variety of unstructured data such as e-mails, reports, presentations, voice mail, photographs, videos, instant messages, blogs, tweets, and Facebook postings (Mann 2010; Robb 2004). Estimates show that about 85  percent of data are now unstructured and this amount is doubling every year (Mann 2010). Furthermore, it is coming from a much broader range of devices and channels, such as mobile phones, social media apps, and tablets. And the focus group is already anticipating the need to be able to capture and exploit information from the physical value chain through RFID tags and other devices. IT managers in the group feel it is important for them to be able use IT tools and skills to capture, manage, and exploit these new forms of information for their businesses.

2. Changing information needs. The focus group also felt strong pressure from the business side of the organization to do a better job of delivering just-in-time information. “Our executives are screaming for data,” said one. “But we really don’t know what they need in order to run the business.” Increasingly, informa- tion needs to be presented in different and more holistic views, rather than in traditional reports. For example, the shift toward enterprise thinking is driving the demand for enterprise information. Executives want the “big picture” on their products and customers. “We need to have a 360° view of our customer,” said one manager. There is also a need to be able to explore data differently— to uncover new patterns and trends and to do different kinds of analysis on it (Chowdhury 2011). “Our business is pressing to have data served differently,” said a manager, noting the proliferation of “data marts” in his organization, each with a different subset of the same data. Furthermore, the enormous amounts of data available are simply too difficult to comprehend without better analysis and presentation. Without this, technological support managers’ ability to use data effectively for decision making and innovation is impaired (Hemp 2009; Shen 2011).

Finally, there is a growing recognition among business executives that organiza- tions that are “sophisticated exploiters of data and analytics” are three times more likely to be top performers than others (Hopkins et al. 2010). While not mentioned expressly by the focus group, research is consistently showing that more effective use of infor- mation affects both company performance and customer satisfaction ( Davenport and Harris 2007; Marchand et al. 2001).

the challenge of BUsiness intelligence

Although there was little disagreement about what effective BI looks like and its value, the focus group and researchers also recognize that this vision is extremely difficult to attain. “Few executives receive the information they say they could use,” one study noted (McGee 2004). Another found that while 9/10 companies say BI is strategic to

210 Section III • IT-Enabled Innovation

them, virtually none (2 percent) have a BI strategy (Bitterer 2010). A third compared how well companies believe they are doing with BI (4.5/10) with how well experts feel they are doing (2.2/10) (Hopkins et al. 2010).

Focus group members cited a number of obstacles they face in helping their com- panies improve BI. These include the following:

• Perspective. One of the biggest challenges said the group is changing organiza- tional mind-sets and culture regarding data. “We’ve never looked at data this way and so we don’t know what we want to be,” said a manager. “Our managers still stress intuition, not facts and their focus is local, not enterprise,” said another. A third manager cited disagreements between business units seeking to better understand the company’s customers. “Instead of working together to come up with a com- mon definition of ‘customer,’ they are all fighting about who ‘owns’ the customer,” he said. BI experts concur that business perspectives need to change. “There is a huge  chasm between leveraging information as an enterprise asset and predicting future outcomes through deep data analysis . . . and reviewing reports and making reactive decisions” (Mohanty 2011).

• Lack of business knowledge. Group members stressed the need to truly under- stand business data and the context in which it is generated. “We need to get at the real questions and develop the right questions,” said one manager. Another explained “we are struggling to understand the real meaning of pieces of data. For example, we have many different meanings of the term ‘in-stock’ in our business, so we need to figure out what this means before we can provide good information on whether or not items are in-stock.” Both business and IT leaders tend to lack knowledge and skills about how best to use BI to improve the business (Hopkins et al. 2010). “We don’t know what we don’t know and it’s difficult to be perceptive about BI without a full range of knowledge,” said a manager.

• Lack of sponsorship and accountability. In spite of the demand for better infor- mation, businesses have been slow to invest in BI. “It’s still not a priority at senior levels,” a manager explained. Without funding and sponsorship, IT is finding it difficult to develop effective data governance mechanisms. “BI is a significant cost and it’s an uphill battle to sell a structured approach,” explained a group member. “We have no executive accountable for BI and no common governance or data defi- nitions so data can’t be reconciled. This leads to everyone doing their own thing.” “We have the ‘wild west’ out there!’,” said another.

• Silo thinking. Traditional silo thinking has been exacerbated by the lack of gover- nance and enterprise perspective and has resulted in fragmentation and duplication of data. “We have spreadsheets everywhere!” said one manager. “Everyone’s going for local optimization.” Group members explained that many business partners are frustrated with the inflexibility of standard data warehouses. As a result, they build their own “data marts” containing the information they alone need and these have limited utility and availability across business functions. “Control versus flexibility with data is an ongoing issue,” said one member.

• Lack of BI skills. BI sits squarely between the IT function and business and requires both business and technical skills, a combination that is hard to find. Focus group members explained that a BI skillset requires competencies in data management, analytics, BI tools, statistics, thought leadership, and

Chapter 15 • Building Business Intelligence 211

interpretation of data. This is consistent with studies that have shown that companies lack analytics and interpretive skills to use BI strategically or com- petitively (Hopkins  et al. 2010). “We need to revalidate our interpretations to understand which data are best and we need a model for interpreting patterns and trends that is consistent across the business,” said a manager. “We must feel comfortable with our models and interpretations and then integrate context.”

the role of it in BUsiness intelligence

As with so much else in IT in recent years (e.g., e-business, social media, and strategic applications), the focus group stressed that successful BI requires active business involvement at all levels. The experts have surprisingly little to say about IT responsi- bilities for BI; many simply assume that the right technology with the right data will be there for the business to work with. Ideally, there is broad consensus that IT provides the “heavy lifting” of BI work, while the business provides the knowledge of what is needed and ability to manipulate and interpret data to provide intelligence (Hostmann et al. 2009). However, the reality in many companies is that “the business has abdicated thought leadership on BI to IT,” a manager stated. Typically, in the focus group, IT is taking the initiative on BI just to get it started. “We are working on building the founda- tions for BI,” said one manager.

There is a clear gap between the disciplined approaches IT feels are needed to “bring it all together for the common good” and the “get it done now” demands for particular information made by business leaders (Meehan and Roberts 2010). Thus, while IT staff try to view the BI picture holistically, with strategies, architectures, models, data definitions, taxonomies, and governance, the business partnerships, vision, and interpretive skills also needed are often lacking (Mohanty 2011). In business, “data is [still] too often seen as a technology issue, rather than a business asset” (Mann 2010).

BI cannot be implemented on any scale without technology and IT organizations are still coming to terms with the scope and complexity of the issues involved in creat- ing common data, managing it effectively, and delivering it to multiple functions and layers in the organization. It is impossible to cover these topics in depth here, so this section simply provides a high-level overview of the major IT activities that contribute to successful BI. All too often, these are either not visible to others in the organization or the effort involved in accomplishing them is not well understood.

The focus group identified four sets of IT activities that together form the founda- tion of IT’s role in BI:

1. BI strategy and planning. Although focus group members understood the gen- eral vision for BI, most didn’t have a clear strategy or roadmap for how to achieve it in their organizations. A BI strategy is broader and more business focused than an information strategy and architecture. Since its stakeholders are almost every- one in the organization, BI plans and strategies need to be inclusive at the high level, recognizing the widely diverse types of BI and their value, and incorporat- ing governance to focus resources on enterprise priorities. Both IT and business need to be part of this process because BI must integrate both with other business strategies and with the technology and information architectures used by IT to guide its work (Bitterer 2010). Focus group members believed that at this point

212 Section III • IT-Enabled Innovation

in its evolution, BI strategy and planning is more likely to be an exploratory and iterative process that helps focus the organization in this area, rather than a formal process that is prescriptive in nature.

2. Data acquisition and management. There is still much to be done in simply understanding and improving the data that already exist in most organizations, said the focus group. Duplicate data, multiple data marts, and inflexible data ware- houses that cannot incorporate new forms of data, are the norm for many. “Much useful data lies in spreadsheets that are all over our organization,” said a man- ager. “People don’t trust our data warehouse,” said another. The “holy grail” of IT is to have a single authoritative source for all data. Thus, most have master data management and data definition initiatives to work on their core structured data. Beyond this, focus group members are streamlining their applications to reduce duplicate data stores and revisiting their data warehouse strategy and technolo- gies to make them more useful. Data architectures are being developed to minimize redundancy and incorporate new types of data. And increasingly, external data— both structured and unstructured—will need to be part of data architectures and plans, as will real-time data. Focus group managers recognized that they will not be able to control all data but they felt strongly that core company data need to be bet- ter managed. “Our goal is to have a governed space that is managed tightly,” said a manager, “and a user-defined space that allows the business to play with data in any way they want.”

3. Information management. This involves improving the value that can be obtained from data by developing a framework within which information can be developed from it. It includes information architecture, data integration, aggregation, context (metadata), quality, governance, security, and privacy activities. Building trust in information is a key driver of this work (Bitterer 2010). “If we are going to make busi- ness decisions based on information, we need to trust that it’s accurate,” explained a manager. Usefulness is also essential and better understanding of business needs is necessary before this can be developed. Information is typically provided in reports, dashboards, and subject area infomarts. Unfortunately, much information in organi- zations is not used and there is still no clear understanding of what makes it useful (Davenport and Snabe 2011). As we have noted elsewhere, high quality informa- tion management must be a collaborative effort between business and IT, incorpo- rating attention to information behaviors (e.g., sharing), risks, value, and roles and accountabilities (e.g., data stewardship) (see Chapter 11).

4. Intelligence delivery. IT has long been responsible for the basics of information delivery, that is, reports and dashboards, and for providing the data warehouses against which queries can be run and historical analysis done. More recently, the knowledge management movement sought to enhance organizational processes and services with useful knowledge that would make them easier to perform, pro- vide decision support, or add value (Smith et al. 2006). However, most organiza- tions have not yet been able to take the next step to use information strategically or do real-time or predictive analysis (Bitterer 2010; Chowdhury 2011). New tools are therefore needed to help them model, interpret, and present information so it can be used to solve business problems and make business decisions (i.e., to create intelligence). Intelligence delivery cannot be done in a structured way, agreed the focus group, because the business environment is simply too dynamic. This is the

Chapter 15 • Building Business Intelligence 213

core of the challenge of BI, they believe, because while IT can provide the data, the tools to manipulate it, and the mechanisms to present it effectively, they are still not asking the right questions or doing the right analysis to understand how intel- ligence can best be delivered and to whom (Davenport and Snabe 2011; Hostmann et al. 2009). Until this happens, intelligence delivery will likely be plagued by the “knowing–doing” gap, in which clear links are not made between information and desired actions (Pfeffer and Sutton 2000).

improving BUsiness intelligence

Although there are pockets of BI excellence in many organizations and some companies that are actually competing on it, for most, improving BI remains an iterative, evolution- ary process rather than a straight line journey (Bitterer 2010; Davenport and Harris 2007). Unfortunately, a company’s information maturity may not equate to a strong BI capability (Finneran and Russell 2011). Although the first is foundational, culture, perspective, skills, and decision processes all need to be addressed to be able to use information intelligently for business decisions and competitive advantage (Mohanty 2011). Although there are no textbook answers about how to improve BI, the focus group and research are beginning to discover practices that can help move companies in the right direction:

1. Learn from the past. If the failure of knowledge management has taught us anything, it is that it is not easy to influence how people use information for decision making or to change what they do:

One of the main reasons that knowledge management efforts are often divorced from day to day activities is that the [people] who design and build the systems for collecting, storing and retrieving knowledge have limited, often inaccurate views of how people actually use knowledge in their jobs. (Pfeffer and Sutton 2000)

All too often, incorrect assumptions are made about what information is wanted or needed in a given activity (McGee 2004). Therefore, learning about how people utilize knowledge for action and then using this as the basis for improv- ing an organization’s intelligence is critically important for successful BI. The key to delivering useful knowledge for action is developing the links between a direct action in a specific setting and the information that can drive or facilitate it (Dixon 2000). The most effective way to do this is to build linkages backward from a specific desired action in a core capability toward the acquisition and packaging of targeted intelligence for a specific group in ways that it finds useful. Though this may seem like common sense, “it is interesting how uncommon, common sense is in its imple- mentation” (Pfeffer and Sutton 1999).

2. Have a strategy for continuous improvement. Organizations need a strategy for making sure that intelligence continues to be useful and used. Companies are typi- cally littered with databases that no one uses because they are out of date or not complete. Successful BI initiatives consistently anticipate the need to maintain and improve the quality and type of information provided as their users learn more about what is possible, useful, and practical to do (Smith et al. 2006). For example, as one organization learned what information people would like to know about

214 Section III • IT-Enabled Innovation

others in the organization, it made an increasing number of connections to new sources of information (e.g., availability, skills). Ultimately, this BI application has now become a key tool in the globalization of the firm’s work. Ideally therefore, BI should evolve as methods of gaining insights improve (Ball 2010). As a focus group manager noted, “you must stay flexible and be willing to change the tool to fit working with people.”

3. Focus. “Implementing BI can be like trying to boil the ocean,” said one manager. “It’s impossible.” Clear focus on targeted pain points where BI can make a differ- ence is therefore essential, agreed the focus group. Successful initiatives take “a relentless focus on a very limited set of burning business questions to guide users to BI-enabled decisions with maximum impact” (Roberts and Meehan 2010). Within this targeted area, it’s best to bring multiple points of view to bear on the issue at hand. For example, Proctor and Gamble did a large statistical survey to under- stand its customers’ needs but also sent employees out to live with families to learn about them first hand and in context (Kanter 2011). By focusing on a goal, it is also easier to target the specific data that are needed and how these might be changing over time (Ball 2010). Finally, focus helps to bring executive attention to bear on the value being delivered by BI, which can result in improved sponsorship and resources (Hemp 2009).

4. Cross-functional governance. It should not be surprising to learn that cross- functional governance is needed for BI initiatives, which tend to have broad organizational scopes. Most members of the focus group mentioned developing effective governance processes as being central to BI success. What is important to note is that such processes are required at several different levels and also need to be integrated with one another. For example, data governance is needed to develop data definitions and come to a “single version of the truth” for core company data. Strong governance is also needed for information management practices, such as determining acceptable levels of risk, privacy and security, how to deal with regulatory matters, and determining what is core and noncore data. Finally, BI governance is needed to focus BI and develop a plan for its evolution. With the increasing use of external sources of data in BI processes, decisions also need to be made about whether or not to trust a source and how use of this data could have strategic implications for an organization (e.g., if it is no longer produced or if the company producing it decides to charge for it).

5. Acquire new IT and analytics skills. More than any other aspect of IT work, BI requires the integration of technology and business knowledge to be successful, said the focus group. “We will need a collaborative BI team in IT at all times,” one manager stated, “because we need to understand business data deeply.” Furthermore, if IT is to lead and facilitate BI, at least initially, as many believe, IT staff will need the skills to bridge the gap between traditional business and technical areas of expertise (Hostmann et al. 2009; Schlegel 2010). And while good BI requires the right people asking the right questions, it also needs the right information and tools to do the job successfully (Gassman et al. 2010). Other skills that will need to be acquired under the “BI umbrella” whether in the business or within IT, include improved analytics skills to test hypotheses, predict future trends, and discover new patterns in data; improved visualization and simulation skills to present information effectively; and the ability to utilize these insights

Chapter 15 • Building Business Intelligence 215

in decisions, new products, services, and strategies. People with these capabili- ties are hard to find and BI skills will need to be developed internally as well as acquired if BI is to be used proactively rather than reactively.

6. Take process views. Both decision making and innovation can be viewed as pro- cesses that connect the organization horizontally (Ball 2010; Roberts and Meehan 2010). Ideally, the more BI can be embedded in processes, the more likely it is to be effective (Shen 2011). As already noted, such processes are complex blends of insight, information, and behavior that a BI team is more likely to get wrong before it gets right (Kanter 2011). The key to success is to focus on a process that really matters to the business and to design the analytic capabilities needed to enhance it. Agile development processes are ideal because these let a BI capability evolve as new insights emerge (Ball 2010). Some aspects of a process that could benefit from BI include reducing event-to-decision latency, automating common analysis tasks, ensuring consistent analysis, and capturing and reusing expert knowledge (Davenport and Snabe 2011; Mohanty 2011).

7. Move from the inside out. BI is likely to be more successful if it grows organically rather than as a one-time comprehensive initiative (Mohanty 2011). Many focus group organizations are already doing BI in smaller ways at a business unit level and are looking for ways to incorporate enterprise and external data to make what they are doing more useful. This is an effective strategy, given most organizations’ lack of sophistication in this area (Hopkins et al. 2010). Managers need to recognize that BI is still maturing and take an experimental approach to its use in business, while at the same time working on the foundational data and information that will be needed to make it successful (Gassman et al. 2010; Mann 2010).

8. Tell stories to articulate value. The value of BI is still unclear, said the focus group and it is hard to document it with quantitative benefits. “The best way to capture the value of BI is through stories told by the business,” said one manager. This con- clusion is very much in keeping with the conclusions of knowledge management experts (e.g., Denning 2005; Nonaka and Takeuchi 2011), who believe that the com- plex benefits of higher order knowledge are best articulated qualitatively rather than quantitatively.

9. Watch out for implementation. Too often, managers become dependent on the explicit aspects of BI and forget their context, leading them to invalid conclusions and inappropriate decisions (Nonaka and Takeuchi 2011). There are many ways that BI can be implemented badly. For example, one manager found that “there’s a fine line between customer loyalty and stalking the customer” in her BI work. Immaturity about BI can also lead to bias and “group think” rather than better decision making (Gassman et al. 2010). Novel situations can be dismissed as insignificant and hard- ened preferences get in the way of good decisions (Kanter 2011). Training in how to use intelligence appropriately is therefore essential. For example, some European banks used analytics to identify their most profitable customers and then discarded their least profitable ones. Scandal ensued and governments had to pass legislation to force the banks to accept clients who receive disability and other social support payments (Davenport and Harris 2007). In short, access to intelligence is simply not enough; managers need “practical wisdom” to make prudent judgments. This can be summarized as, “know why; know how; and know what should be done” (Nonaka and Takeuchi 2011).

216 Section III • IT-Enabled Innovation

BI is not a new idea but it is one to which organizations keep returning on a regu- lar basis. This time, the technologies, the data, and the perspective have changed and become broader and more complex, while at the same time enabling an infinite number of new possibilities for supporting organizations with analysis and intelligence. This chapter has clarified some of the similarities and differences between the cur- rent pressures for BI and those of the past and outlined a holistic view of BI that incor- porates both the IT foundations of data and information management and the uses to which these can be put to derive value for

the organization. It is clear that organiza- tions will need to do a better job at all three levels if BI is going to realize its promise. While there is much theoretical value to be gained from BI, the fact remains that there are many complex organizational and behavioral challenges to be addressed before it can be realized. IT has the opportunity to take a leadership role in BI but its ability to do so is limited by how much it understands about the business and its ability to integrate technical and business knowledge to deliver intelligence. Its success in the future will depend on how well it can develop these new capabilities.

Conclusion

Ball, M. “Five Simple Steps to Better Decisions: Your Business Processes Can Lead You to Targeted Variables for Improvement.” Information Management 20, no. 5 (September 1, 2010).

Bitterer, A. “The BI(G) Discrepancy: Theory and Practice of Business Intelligence.” Gartner Inc., ID Number: G00176038, August 2, 2010.

Chowdhury, S. “A Soft Computing Environment for Data Mining.” The Business Review, Cambridge 18, no. 1 (Summer 2011).

Davenport, T. “Analytics 3.0.” Harvard Business Review 91, no. 12 (December 2013).

Davenport, T., and J. Harris. Competing on Analytics: The New Science of Winning. Boston, MA: Harvard Business School Publishing, 2007.

Davenport, T., and L. Prusak. Working Knowledge: How Organizations Manage What They Know. New York: Boston, Harvard Business School Press, 1998.

Davenport, T., and J. Snabe. “How Fast and Flexible Do You Want Your Information, Really?” MIT Sloan Management Review 52, no. 3 (Spring 2011).

Denning, S. The Leader’s Guide to Storytelling: Mastering the Art and Discipline of Business Narrative. San Francisco: Jossey-Bass, 2005.

Dixon, N. Common Knowledge. Boston, MA: Harvard Business School Press, 2000.

Finneran, T., and B. Russell. “Balanced Business Intelligence: Each Level of BI is a Stepping Stone that Adds Capability to Meet Growing User Needs.” Information Management 21, no. 1 (January 1, 2011).

Gassman, B., R. Sallam, A. Bitterer, J. Hagerty, and N. Chandler. “Predicts 2011: New Relationships will Change BI and Analytics.” Gartner Inc., ID Number: G00209225, November 25, 2010.

Hatten, K., and S. Rosenthal. Reaching for the Knowledge Edge. New York: Amacom, 2001.

Hemp, P. “Death by Information Overload.” Harvard Business Review 87, no. 9 (September 2009).

Hopkins, M., S. LaValle, F. Balboni, R. Shockley, and N. Kruschwitz. “Ten Insights: What Survey Reveals about Competing on Information and Ten Data Points: Information and Analytics at Work.” MIT Sloan Management Review 52, no. 1 (Fall 2010).

Hostmann, B., N. Rayner, and G. Herschel. “Gartner’s Business Intelligence, Analytics and Performance Management Framework.” Gartner Inc., ID Number: G00166512, October 19, 2009.

References

Chapter 15 • Building Business Intelligence 217

Kanter, R. “Zoom In, Zoom Out.” Harvard Business Review 89, no. 3 (March 2011).

Mann, J. “Highlights for the Business Intelligence and Information Management Track at Gartner European Symposium/ITxpo 2010.” Gartner Inc., ID Number: G00209468, December 6, 2010.

Marchand, D., W. Kettinger, and J. Rollins. Making the Invisible Visible. Chichester, England: John Wiley & Sons, 2001.

McGee, K. “Give Me that Real-Time Information.” Harvard Business Review 82, no. 4 (April 2004).

Meehan, P., and J. Roberts. “Executive Summary: Business Intelligence and Decision Impact.” Gartner Inc., ID Number: G00200706, May 1, 2010.

Mohanty, S. “Having Analytics May Not Be Enough: Organizations Need to Improve Business Intelligence and Decision-Making through Guided, Predictive Analytics.” Information Management 21, no. 1 (January 1, 2011).

Nonaka, I., and H. Takeuchi. “The Wise Leader.” Harvard Business Review 89, no. 5 (May 2011).

Pfeffer, J., and R. Sutton. “Knowing ‘What’ to Do Is Not Enough: Turning Knowledge into

Action.” California Management Review 42, no. 1 (Fall 1999).

Pfeffer, J., and R. Sutton. The Knowing-Doing Gap. Boston, MA: Harvard Business School Press, 2000.

Robb, D. “Getting the Bigger Picture: Dealing with Unstructured Data.” Datatmation (September 13, 2004).

Roberts, J., and P. Meehan. “From Business Intelligence to Intelligent Business,” Gartner Inc., ID Number: G00208713, November 11, 2010.

Schlegel, K. “Prepare for Customer-Facing Business Intelligence.” Gartner Inc., ID Number: G0020630, October 15, 2010.

Shen, G. “Unplugged: The Disconnect of Intelligence and Analytics.” Information Management 21, no. 1 (January 1, 2011).

Smith, H. A., J. D. McKeen, and S. Singh. “Making Knowledge Work: Five Principles for Action-Oriented Knowledge Management.” Knowledge Management Research and Practice 4, no. 2 (2006).

Stewart, T. Intellectual Capital: The New Wealth of Organizations. New York: Doubleday, 1997.