Decision Support Systems Lecture II Business Intelligence

1. Decision Support SystemsLecture IIBusiness Intelligence Dr. Chattrakul Sombattheera Free Powerpoint Templates

2. 2.1 A Preview of the content • A centralized repository of data, usually the data warehouse (DW). • An end-user set of tools that can be used to create reports and queries from data and information and to analyze the data, information, and reports. This set of tools is referred to as BA and also includes data visualization. • To find non-obvious relationships among large amounts of data, We can use a statistical-mathematical approach known as data mining. For text, We can use text mining, and for Web data, we can use Web mining; all of these are described. The statistical tools and the methodology for mining, including neural computing. • To gain a competitive edge, companies need to be innovative and to excel. In order to find out how well a company is performing today, Where it wants to go, and how to get there, we can use a methodology referred to as BPM . It includes setting up goals as metrics and standards and monitoring and measuring performance by using the BI methodology.

3. 2.2 The origins and drivers of business intelligence (BI) Table 2.1 Business Value of BI Analytical Application

4. 2.2 The origins and drivers of business intelligence (BI) Table 2.1 Business Value of BI Analytical Application

5. 2.3 THE GENERAL PROCESS OF INWELLIGENCE CREATION AND USE • Managers and executives need BI solutions to better manage the business. Enterprises that fail to properly implement these solutions put themselves at a competitive disadvantage. To be successful in today’s business environment, enterprises must: • Assess their readiness for meeting the challenges posed by these new business realities • Take a holistic approach to BI functionality • Leverage best practices and anticipate hidden costs • Gartner, Inc. (2004), suggested the following key questions as a framework for BI analysis: • How can enterprises maximize then BI investments? • What BI functionality do enterprises need, and what are they using today? • What are some of the hidden costs associated with BI initiatives?

6. 2.3 THE GENERAL PROCESS OF INWELLIGENCE CREATION AND USE • An example of how BI helped a company deal with the Sarbanes-Oxley Act of 2002 is provided next (extracted from Gartner, Inc., 2004). • Example • The Sarbanes-Oxley Act of 2002 mandates drove one firm to implement a new financial performance management system, capable of meeting the new requirements to: • Perform flawless analysis and compilation of thousands of transactions and journal entries. • Balance more access to data with the need to control access to sensitive insider information. • Deliver reports to the SEC in less time.

7. 2.3 THE GENERAL PROCESS OF INWELLIGENCE CREATION AND USE • The company deployed a BI infrastructure and applications that met these challenges. Within the overarching goal of achieving financial-reporting compliance, these objectives included the following: • Get "more eyes on the data" and key performance indicators and build in strict security controls • Provide live reports that allow people to drill down to the lowest level of transaction detail • Put a spotlight on the accounting treatment of material components • Proactively scour the financial databases for anomalies, using variance triggers • Gather all financial data into a cohesive database • An implementation tightly linked to these objectives provided the company with a financial performance management system that enables analysis to complement accounting and budgeting applications for flexible reporting, free-form investigation, and automated data analysis. The BI infrastructure and applications support large numbers and types of users and uses automatic data mining for anomaly detection. It can proactively alert specific individuals whenever an anomaly is detected.

8. 5.3 THE GENERAL PROCESS OF INWELLIGENCE CREATION AND USE A CYCLICAL PROCESS Process of Intelligence Creation and Use

9. 2.3 THE GENERAL PROCESS OF INWELLIGENCE CREATION AND USE • INTELLIGENCE CREATION AND USE AND Bl GOVERNANCE • For each potential BI project in the portfolio, it is important to use return on investments (ROI) and total cost of ownership (TCO) measures to estimate the cost-benefit ratio. • This means that each project must be examined through costing associated with the general process phases as well as costs of maintaining the application for the business user. • In addition, the benefits estimations need to involve end-user examinations of decision-making impacts, including measures reflecting benefits such as cash flow acceleration. • Some organizations refer to the project prioritization process as a form of BI governance (see Matney and Larson, 2004; and Online File WS.2). • A typical set of issues for the BI governance team is to address the following: • Creating categories of projects (e.g., investment, business opportunity, strategic, mandatory) • Defining criteria for project selection • Determining and setting a framework for managing project risk • Managing and leveraging project interdependencies • Continually monitoring and adjusting the composition of the portfolio

10. 2.4 THE MAJOR CHARACTERISTICS OF BUSINESS INTELLIGENCE • TRANSACTION PROCESSING VERSUS ANALYTIC PROCESSING • Enterprise software system are designed as transaction processing tools, and today the main job is to optimize an informed decision-making process for users at all levels of the organizational hierarchy. • Recent trends seem to indicate that access to key operational data is no longer the purview of executives alone. • Many executives of manufacturing and service companies today are allowing (and even encouraging) low-level managers, supervisors, and analysts on the shop floor and in distribution centers access to operational performance data, to enable better and more timely decision making by those employees. • The transaction processing systems involved with these transaction constantly handle updates to what we might call operational databases. Example, an ATM withdrawal transaction needs to reduce the bank balance accordingly, a bank deposit adds to an account, and a grocery store purchase is likely reflected in the store’s calculation of total sales for the day and should reflect an appropriate reduction in the store’s inventory for the items we bought. • These online transaction processing (OLTP) systems handle a company’s ongoing business. • We will provide a more technical informed definition of DW; at this point, it suffices to say that DWs are intended to work with informational data used for online analytical processing (OLAP) system.

11. 2.4 THE MAJOR CHARACTERISTICS OF BUSINESS INTELLIGENCE • TRANSACTION PROCESSING VERSUS ANALYTIC PROCESSING • Most Operational data in enterprise resource planning (ERP) system ---and in their complementing siblings, such as supply-chain management (SCM) or customer relationship management (CRM), are stored in what is referred to as OLTP system, which are computer-processing systems in which the computer responds immediately to user requests. • The very design that makes an OLTP system efficient for transaction processing makes it inefficient for end-user ad hoc reports, queries, and analyses.

12. 2.4 THE MAJOR CHARACTERISTICS OF BUSINESS INTELLIGENCE • THE INFORMATION FACTORY VIEW • The term warehouse is associated with the concept of a factory. • The information factory View sees BI/DW as a central, critical component of any business organization (corporate or government), and today it is moving more and more toward the Web environment (see Inmon, 2005). • As with a physical factory, with an information factory, there are inputs (e.g., data sources, acquisition), storage (e.g., DW, data marts), processing of inputs (e.g., analysis, data mining), and outputs (e.g., data delivery, BI applications). • An information factory is connected to other internal information systems, such as ERP, CRM, and e-commerce, as Well as to external information systems, usually via the Internet or an extranet. The information factory concept is illustrated in Figure S.2.

13. 2.4 THE MAJOR CHARACTERISTICS OF BUSINESS INTELLIGENCE • DATA WAREHOUSING AND BUSINESS INTELLIGENCE • A DW is a collection of data, designed to support management decision making. DWs contain a wide variety of data that present a coherent picture of business conditions at a single point in time. The theory was to create a database infrastructure that is always online and that contains all the information from the OLTP systems, including historical data, but reorganized and structured in such a way that it is fast and efficient for querying, analysis, and decision support.

14. 2.4 THE MAJOR CHARACTERISTICS OF BUSINESS INTELLIGENCE • TERADATA ADVANCED ANALYTICS METHODOLOGY • Teradata, a division of NCR (teradata.com), created a methodology for BI that is illustrated in Figure S.3. As shown in the figure, BI applications (upper-left side) are supported by advanced analytics techniques and tools (left side). The methodology is shown on the right side as a cyclical process that circles the enterprise DW. The process includes steps such as business understanding and data understanding (right side of figure).

15. 2.4 THE MAJOR CHARACTERISTICS OF BUSINESS INTELLIGENCE TERADATA ADVANCED ANALYTICS METHODOLOGY The Corporate Information Factory

16. 2.4 THE MAJOR CHARACTERISTICS OF BUSINESS INTELLIGENCE TERADATA ADVANCED ANALYTICS METHODOLOGY Teradata Advanced Analysis Methodology

17. 2.5 TOWARD COMPETITIVE INTELLIGENCE AND ADVANTAGE • STRATEGIC IMPERATIVE • BI projects have shown significant business value to organizations (see Williams and Williams, 2003). • First, in many markets, “barriers to entry of a new competitor to an industry” (see Porter, 1985) are being significantly diminished. • This means that an organization that has a strong position within its industry could easily face new competitors because the costs and other constraints to becoming a player in the market have decreased. • This is due to increasing globalization, as companies from around the world are challenging major players in industries such as automobile manufacturing, electronics, textile manufacturing, and computer software development, just to name a few. • Furthermore, the ability to deliver goods throughout the world through readily available supply-chain channels such as FedEx, UPS, and DHL, as well as e-commerce, is making it easier for potential competitors to get products and services to more customers almost anywhere.

18. 2.5 TOWARD COMPETITIVE INTELLIGENCE AND ADVANTAGE • COMPETITIVE INTELLGENCE • Although CI often involves more than the BI initiatives used in most organizations, there are some important overlaps. • One difference between CT and BI is that CI implies tracking what competitors are doing by gathering sources of materials on their recent and in-process activities. • In BI initiatives, some outside sources of data are included in the analysis process, but they are often available from third-party vendors. • Members of the Society of Competitive Intelligence Professionals (scip.org) view BI as an emerging aspect of their overall charter, which typically includes more generic competitor analysis.

19. 2.5 TOWARD COMPETITIVE INTELLIGENCE AND ADVANTAGE • CEMPETITIVE STRATEGY IN AN INDUSTRY • Competitor analysis is a component of industry analysis, which serves as a basis for strategic planning processes. • Competitive intelligence in this context would imply that companies need to know if some major new means of producing/generating/delivering a service or product would result in significantly lower costs, thereby shifting the competitive landscape. • BI applications in this context might include scrutinizing quality metrics associated with specific production processes, analyzing raw materials from various suppliers to assess defect rates, tracking costs of goods sold as a percentage of rut volume, and so on. • In addition, BI applications can generate business rules can actually be integrated with business processes. • Another competitive strategy is to focus on a particular market niche, perhaps through some form of product or service differentiation. • This means that a specific market segment that has a special preference, perhaps for upscale goods and services, would be the target of the strategy. • For example, having a hotel room prepared according to a business traveler’s common wishes, with the appropriate newspaper delivered in the morning, might be a way to build loyalty to serve a lucrative market niche.

20. 2.5 TOWARD COMPETITIVE INTELLIGENCE AND ADVANTAGE • SUSTAINING COMPETITIVE ADVANTAGE • Organizations do this through building brand and customer loyalty, for example, through BI applications for product differentiation/market niche strategies. • Most strategic analysts agree that low-cost leadership may not yield a sustainable advantage unless the low cost can be sustained. • For this reason, BI projects and DW are becoming increasingly important weapons in sustaining competitive advantage across industries; the type of BI projects might vary based on strategy, and, in particular, the BI governance team might prioritize potential projects based on their ability to offer sustained competitive advantage.

21. 2.6 THE TYPICAL DATA WAREHOUSE AND BUSINESS INTELLIGENCE USER COMMUNITY • Which personnel in an organization would be the most likely to make use of BI? One of the most important aspects of a successful DW/BI initiative is that it must be of benefit to the enterprise as a whole. This implies that there are likely to be a host of users in the enterprise, many of whom should be involved from the outset of a DW investment decision. Not surprisingly, there are likely to be users who focus at the strategic level and those who are more oriented to the tactical level. An appropriate framework for describing user communities is to discuss the following categories: farmers, tourists, operators, explorers, and miners (suggested by Imhoff and Pettit, 2004). The details are provided in Online File WS.3.

22. 2.6 THE TYPICAL DATA WAREHOUSE AND BUSINESS INTELLIGENCE USER COMMUNITY • Table 2.2 Matching User Types and Functionality to Maximum Value

23. 2.6 THE TYPICAL DATA WAREHOUSE AND BUSINESS INTELLIGENCE USER COMMUNITY • Gartner, Inc.(2004), distinguishes six similar types of users. Table 2.2 shows these different users, how many these are, what BI tools they use, and the strategic value of their usage. • The various classes of DW and BI users that exits in an organization can help to guide how the DW is structured and the types of BI tools and other supporting soft-ware needed. Members of each group are excellent sources of information on assessing the costs and benefits of specific BI project when a DW is in place.

24. 2.7 SUCCESSFUL BUSINESS INTELLIGENCE IMPLEMENTTATION • Gartner, Inc.(2004), prepared a comprehensive report regarding the implementation of BI and its relationships to other enterprise systems, such as ERP and CPM; this report also provides interesting case studies. The report covers the following major topic: • -BI trends and technologies • -Effective BI approaches for today’s business world • -Organizing for BI success • -Best practices for defining effective business metrics • -Building an agile infrastructure for strategic BI • -The benefits of effective data quality and metadata management • -Management costs and enhancing value of DW and BI • -Business trends and best practices in managing corporate performance • -The BMP road map • -Key trends in corporate governance and compliance management • -Using business activity monitoring to gain a real-time edge • -Getting the most out of ERP through BI

25. 2.7 SUCCESSFUL BUSINESS INTELLIGENCE IMPLEMENTTATION • -The role of analytics in successful CRM strategies • -Web analytics: From software to service model • -Driving workplace productivity with portals and enterprise suites • If a company’s strategy is properly aligned with the reasons for a DW and BI initiatives, if the company’s IS organization is or can be made capable of playing its role in such a project, and if the requisite user community is in place and has the proper motivation, it is wise to start BI and establish a BI competency center (BICC) within the company. What can a company’s BICC achieve? Following are several potential achievements, as exemplified by France • -The center can demonstrate how BI is clearly linked to strategy and execution of strategy. • -The center can serve to encourage interaction between the potential business user communities and the IS organization. • -The center can serve as a repository and disseminator of best BI practices between and among the different lines of business. • -Standards of excellence in BI practices can be advocated and encouraged throughout the company.

26. 2.7 SUCCESSFUL BUSINESS INTELLIGENCE IMPLEMENTTATION • -The IS organization can learn a great deal through interaction with the user communities, such as knowledge about the variety of types of analytical tools needed. • -The business user community and IS organization can better understand why the DW platform must be flexible enough to provide for changing business requirements. • -The BICC can help important stakeholders, such as high-level executives, see how BI can ply an important role • For more on BICC, see Gartner, Inc. (2004)

27. 2.7 SUCCESSFUL BUSINESS INTELLIGENCE IMPLEMENTTATION • France Telecom Business Intelligence • In a short period of time, France Telecom transitioned from being France's only telecom provider to one of several in an industry that was becoming deregulated. With new competitors rapidly entering the telecom market, France Telecom’s executives knew they had to use their information systems as a major strategic weapon. They initiated a repositioning under the banner of becoming the “Net Company.” This required substantial rethinking to foster information systems standardization throughout the company and its subsidiaries. To this end, they set out to migrate all applications to a technical architecture more suitable for Web-based capabilities. In the past, the company had been organized on a regional basis, with each regional business unit management its own IT budget. This led to the coexistence of a myriad of dissimilar technologies, applications software versions, and so on. • Standardization was a first step in laying an infrastructure foundation for a major DW and BI initiative. The company established a four-person team to facilitate its BICC. The BICC was charged with overseeing the data warehousing implementation, ensuing that different business unit and BI teams share best practices, and maintaining consistency in all BI-related projects. The BICC was responsible for several import task. First, the BICC was charged with providing consulting and development services, including offering advice to project managements on development strategies with respect to design,

28. 2.7 SUCCESSFUL BUSINESS INTELLIGENCE IMPLEMENTTATION • France Telecom Business Intelligence • auditing, installation, and so on. Second, the BICC provided support for project managers, architects , designers, developers, and operators via a hotline and help desk. Support also included an intranet Web site to provide BI tool advice, tips, methodology advice, and installation documentation. Next, the BICC was the designated negotiator for the company with BI vendors. The BICC centralized the opening of all case new software versions; and tracking, distribution, and maintenance of license arrestment. Finally, he BICC helped support end users with tools to help them become more autonomous, including an intranet site dedicated to user support, online training, and interaction help. The intranet site was also used to disseminate information on BI success stories (i.e., project that resulted in superior performance in line with the company’s strategy and objectives). To that end, the site was a source of information for executives on the state of the BI initiative in delivering business value. • In summary, France Telecom’s BICC was developed to help the organization manage its portfolio of BI projects, standardize analytical approaches across the enterprise, train and educate end users, help power users, provide knowledge management through the sharing of best practices, and handle all associated vendor relations and support.

29. 2.7 SUCCESSFUL BUSINESS INTELLIGENCE IMPLEMENTTATION France Telecom Business Intelligence France Telecom’s service to more than 91 million customers in 220 countries on 5 continents has been significantly enhanced through its DW and ongoing BI projects. As an example of executive leadership’s support for the BICC and its initiatives, the director of operations for Customer Relations Information Systems stated, “To win new customers and develop loyalty, we now base our action on a business intelligence process in which BI plays a key role of retrieving and analyzing data in our corporate resources. Today, the company has 130,000 PCs, nearly half of which run BI software.”

30. 2.7 SUCCESSFUL BUSINESS INTELLIGENCE IMPLEMENTTATION ATTAINING REAL-TIM, ON-DEMAND BI The demand for instant, on-demand access to dispersed information has grown as the need to close the gap between the operational data and strategic objective has become more pressing. As a result, a category of product called real-time BI applications have emerged. The introduction or new data-generating technologies, such as RFID, is accelerating this growth and the subsequent need for real-time BI. Traditional BI systems use a large volume of static data that have been extracted, cleansed, and loaded into a DW to produce reports and analyses. However, he need is not just reporting because users need business monitoring, performance analysis , and an understanding of why things are happening. These can alert users, virtually in real-time, about changes in data or the availability of relevant report, alerts, and notifications regarding events and emerging trends in Web, e-mail, or instant messaging (IM) applications. In addition, business applications can be programmed to act on what these real-time BI systems discover. For example, an SCM application might automatically place an order for more “widgets” when real-time inventory falls below a certain threshold, or a CRM application might automatically trigger a customer service representative and credit control clerk to check a customer who has placed an online order larger than $10,000

31. 2.7 SUCCESSFUL BUSINESS INTELLIGENCE IMPLEMENTTATION ATTAINING REAL-TIM, ON-DEMAND BI The first approach to real-time BI user the DW model of traditional BI system. In this case, products from innovative BI platform providers such as Ascential (ascential.com) or Informatica (informatiea.com) provide a service-oriented, near-real-time solution that populates the DW much faster than the typical nightly extraction, transformation, and load (ETL) batch update does. The second approach to real-time BI is commonly called business activity monitoring . This appriach is used by pure-play BAM and hybrid BAM middleware provider such as Savvion (savvion.com), Integration Software(itteration.com), Vitria(vitria.com), webMethods(webmethods.com), Quantive(quantive.com) , and Tibco (tibco.com), It bypasses the DW entirely and user web services or other monitoring means to discover key business evens. These software monitors (or intelligent agens) can be placed on a separate server in the network or on the transactional application databases themselves, and they can use event- and process-based approaches to proactively and intelligently measure and monitor operational processes. Also, the use of the Web facilitates real-time BI, see Thompson and Jakovljevic (2005)

32. 2.8 STRUCTURE AND COMPONENTS OF BUSINESS INELLIGENCE THE DATA WAREHOUSE Data flow from operational systems (e.g., CRM , ERP) to a DW, which is a special database or repository of data that has been prepared to support decision-making applications ranging from this for The Major Components of Business Intelligence

33. 2.8 STRUCTURE AND COMPONENTS OF BUSINESS INELLIGENCE THE DATA WAREHOUSE simple reporting and querying to complex optimization. The DW is constructed with methodologies, mainly metadata and ETL. Also described there are data marts, which are repositories of a particular subject or department (e.g., marketing). BUSINESS ANALYTICS Many software tools allow users to create on-demand reports and queries and to conduct analysis of data. They appear originally under the name online analytical processing (OLAP). For example, users can analyze different dimensions of multidimensional data , such as time series and trend analysis views. Hence, business users can quickly and easily identify performance trends by using time-phased information analysis and graphing capabilities of products that support more sophisticated data analysis and have full calculated field capabilities. To conduct BA, the user needs interactivity software that is called middleware to access the DW. It is considered infrastructure, and it is a user interface to the system.

34. 2.8 STRUCTURE AND COMPONENTS OF BUSINESS INELLIGENCE DATA MINING Data mining is a class of database information analysis that looks for hidden patterns in a group of data that can be used o predict future behavior. For example, I can help retail companies find customers who have common interests. However, the term is commonly misused to describe software that presents data in new ways because true data mining software does not just change he presentation but actually discovers previously unknown relationships among the data; this knowledge is than applied to achieving specific business goals. These tools are used to replace or enhance human intelligence by scanning through massive storehouses of data to discover meaningful new correlations, pattern recognition technologies and advanced statistics.

35. 2.8 STRUCTURE AND COMPONENTS OF BUSINESS INELLIGENCE BUSINESS PERFORMANCE MANAGEMENT The final component of the BI process is BPM/CPM. This component is based on the balanced scorecard methodology, which is a framework for defining, implementing if managing and managing an enterprise’s business strategy by linking objectives with factual measures. In other words, it is a way to link top-level metrics, such as the financial information created by the chief financial officer (CFO), with actual performance all the way down the corporate pecking order. BPM uses BI analysis reporting and queries. The objective of BPM is to optimize the overall performance of an organization. Currently, most BI suites enable the application of balanced Scorecards by providing the ability to readily compare business performance with established targets. Such BI suites also provide a platform for sharing performance targets and results across an enterprise, allowing management to understand how the business is performing at a glance. The BPM includes usually dashboards, which provide a comprehensive, at-a-glance, view of corporate performance with graphical presentations resembling an automobile dashboard. Dashboards show performance measures, trends, and exceptions, and they integrate information from multiple business areas. The centerpiece of any dashboard design is captured metrics and performance indicators that are combined to form graphs reflecting the health of the business.

36. 2.9 BUSINESS INTELLIGENCE TODAY AND TOMORROW In today’s highly competitive business, the quality and timeliness of business information for an organization is not just a choice between profit and loss; it may be a question of survival or bankruptcy. No business organization can deny the inevitable benefits of BI. Recent industry analyst reports show that in the coming years, millions of people will use BI visual tools and analytics every day (see Baum, 2006). Today’s organizations are deriving more value from BI by extending actionable information to many types of employees, maximizing the use of existing data assets. Producers, retailers, governments, special agencies, and others use visualization tools, including dashboards. More and more industry-specific analytical tools will flood the market to do almost any kind of analysis and help to make informed decision making from the top level to the user level. A potential trend involving BI is its possible merger with artificial intelligence (AI). AI has been used in business applications since the 1980s, and it is widely used for complex problem-solving and decision support techniques in real-time business application (see Chapters 12-14). It will not be long before AI applications are merged with BI, bringing in a new era in business. To enable this integration, BI vendors are integration (EII). See Thompson and Jakovljevic (2005).

37. 2.9 BUSINESS INTELLIGENCE TODAY AND TOMORROW BI is spreading its wings to cover small, medium, and large companies. Large BI players are for large enterprises, and small, niche players service midsize and small companies. Analytics tools are also penetrating the market for very specialized functions, which will help some companies to go just for BA instead of full DW-based BI implementation. BI takes advantage of already developed and installed components of IT technologies, helping companies leverage their current IT investments and use valuable data stored in legacy and transactional systems. For many large-size companies that have already spent millions of dollars building DW and data marts, now is the right time to build BI as the next step to get the full benefit of their investment, which will directly affect ROI. However, although some components of BI, such as the DW, may change (e.g., data may be stored online), the need for conducting BI in our rapidly changing business environment will increase, making BI a necessity. For more on the future of BI see Lal (2005).