How effective are Business Intelligence (BI) tools for supporting decision-making - Essay Example

? Business Intelligence ID] [Module and Number] [Module It is a unanimous understandingof enterprise executives the world over that the timely and accurate use of knowledge is imperative for the existence and success of any organization. This is because timely and accurate knowledge means improved business performance. The knowledge that is at hand, if handled properly, both in the quantitative and in the qualitative manners, it brings value to the organization’s decision makers. The techniques that assist in the providence of the value of knowledge are knowledge management and business intelligence. An introduction to the basic concept of business intelligence would assist in the further proceedings of the paper. INTRODUCTION TO BUSINESS INTELLIGENCE: Business Intelligence refers to a very comprehensive terminology, often narrated as a combination of ‘data’, ‘information’ and ‘knowledge’. Where, Data: Is a mere collection of raw facts. For example, a company’s daily sales records etc. Information: The organization, analysis and summarization of data that makes it meaningful. Knowledge: Knowledge is the resultant of combination of information with experience, analysis, context and reflections. The resultant form of information, termed as knowledge now, can be utilized by decision makers. The key business terminology of business intelligence, however, has more than just one meaning associated with it. The various meanings it holds correspond to the numerous means in which it can be deployed. Each business holds this entity as its integral part without the inclusion of which it may be potentially impossible to run a business at all. In order to demonstrate the variations in its meaning only two of its various meanings are demonstrated as under. “Business intelligence (BI) is a broad category of application programs and technologies for gathering, storing, analyzing, and providing access to data to help enterprise users make better business decisions. BI applications include the activities of decision support, query and reporting, online analytical processing (OLAP), statistical analysis, forecasting, and data mining.” (Sauder, 2011) and, “Normally describes the result of in-depth analysis of detailed business data. Includes database and application technologies, as well as analysis practices. Sometimes used synonymously with "decision support," though business intelligence is technically much broader, potentially encompassing knowledge management, enterprise resource planning, and data mining, among other practices. ...” (csumb, 2011) Trying to interpret the actual meanings of the term ‘intelligence’ and how it is evolved would give us a better understanding into the terminology of business intelligence itself. Generally, intelligence refers to the ability to understand, learn and evolve. Intelligence develops with every learning experience and input of every kind of information. Basic intelligence, when deployed in business environment is referred to as business intelligence. THE DISCUSSION: The capacity of human beings to incorporate prior instinctive and experience based knowledge to execute processes in order to achieve a particular objective is termed as intelligence. It’s a virtual entity that encompasses all logical horizons. Business is also one of the natural and logical processes. Logic can be defined as a set of rules that governs executions. To discriminate a process as being logical or illogical one needs to be intelligent. This new perspective about intelligence gives a much understandable definition of Business Intelligence. BI would now be defined as, the capacity that enables businessmen to differentiate logical and illogical executions in a business.. This definition presents Business Intelligence as an umbrella that covers almost all the tasks performed under the tag of ‘businesses’. This paper emphasizes on the same notion with the discussion of multiple top notch business terms namely sales forecasting, market research and knowledge management. The association of business intelligence with sales forecasting, knowledge management and Market Research brings new meanings to this seemingly simple business term. It is attempted to take a general look at the basic definitions of each of the above mentioned terms before looking at their comparative involvements and meanings. SALES FORECASTING: Sales forecasting is a well known business terminology. Integral to its existence this business process involves an insight into the future prospects of a company’s sales. These sales may be spanned over any specific amount of time may it be weekly, monthly or yearly. The importance of this vital business process can be assessed by the fact that the prospective production strategies and those involving inventory are all based upon the feedback given to the business by it sales forecasting process. It is impossible that without having an idea of the sales of a business the designing of its inventory be done. Estimates regarding the cash flow in a business and its growth plan are also based upon knowledge input from the sales forecasting business process. Thus, it can very truly be said that information used to make intelligent business processes is gained from sales forecasting only. The procedural steps for forecasting sales of an existing business are far more convenient and simpler than forecasting the sales patterns of a new or proposed system. This is owing to the fact that for an existing business sales forecasting can be done by using trends of sales that existed in the same time month of the last financial year and combining this information with the current existing economic and business trends. Business intelligence plays an integral role in the handling of information in line with the sales forecasting strategies. With reference to its role in sales forecasting Kahn and Adams (2001) quote, “it appears that data are most utilized for sales forecasting, information is most utilized for product forecasting and knowledge is important for enhancing satisfaction in the overall forecasting endeavour. This implies that companies really need to address all three forms of intelligence.” (Kahn, Adams, 2001) KNOWLEDGE MANAGEMENT: This business process refers to a series of steps that involve the creation, spreading out and utilization of knowledge. The term knowledge here refers to the intellectual assets of an organization that are used to enhance its performance and competing power. Two virtual steps constitute the business process of knowledge management. Firstly, the capturing and scripting of knowledge and secondly, its proper distribution into the business fractions concerned so as to gain full advantage of it. --------- quotes in his paper -------- “Both business intelligence and knowledge management perform similar activities in collecting data, organizing the data, analyzing data, aggregating data, and applying data to generate solutions to help make business decisions.  However knowledge management includes two other activities that business intelligence lacks.  These activities are the creation of new knowledge and the dispersion of knowledge throughout an organization.  This is where knowledge management encompasses the activities of business intelligence.” (,) MARKET RESEARCH: "Marketing research is the function that links the consumer, customer, and public to the marketer through information - information used to identify and define marketing opportunities and problems; generate, refine, and evaluate marketing actions; monitor marketing performance; and improve understanding of marketing as a process. Marketing research specifies the information required to address these issues, designs the methods for collecting information, manages and implements the data collection process, analyzes, and communicates the findings and their implications." American Marketing Association (AMA) - Official Definition of Marketing Research The way Business Intelligence is influential in market research is the intelligent handling of information in line with the business process requirements. Business intelligence incorporates the organizational information necessary for the process of market research and enables its successful handling throughout. BI and OLAP: The advent of technological frameworks and the ever expanding World Wide Web have resulted in the input of un-administrable amounts of information into a business. It is essential for every business to adhere to the information that is coming into it as this is vital for its up-to-date process framework and infrastructure. The handling of large amounts of data is done by storing it into large data banks. The systematic storage of data enables its timely retrieval by both business units and workers connected to the organization. This, in turn, enhances the way this information is used to become building blocks of the business itself. This systematic and intelligent storage of data is referred to as data warehousing. Assisting data warehousing is another interactive software based application. Known as OLAP (Online Analytical Processing), this tool has been designed to respond to multiple and complex resolution of queries simultaneously. Being multidimensional in nature, OLAP responds efficiently to complex analytical queries. On a broader scale, OLAP is considered as an integral part of business intelligence as it also gives the provision of relational reporting and data mining. EFFECTIVENESS OF BUSINESS INTELLIGENCE The basic requirement that triggers the implementation of Business Intelligence software is that of the facilitation of better decision making. This better decision making is made possible with the successful flow of information. A software system that makes possible the timely, accurate and efficient transfer of information becomes an integral part of the task flow of an organization. BUSINESS INTELLIGENCE SOFTWARE TRENDS Since Business Intelligence has become an integral part without which it is not possible to successfully run a business set up in today’s challenging world, the innovations of technology have bought forth a number of software that enable the implementation of business intelligence within organizations. As Business intelligence itself is growing at a very rapid rate each year so are the software products supporting it. Following is an account of a number of trends pertaining to the ‘Business Intelligence Software’ that have been noticed recently. PRE-PACKED SOFTWARE SOLUTION This is a combination of solutions that are generic in nature and have been created as an outline within which an organization’s strategic issues can be embedded. Since such software packages cover the strategic issues for an organization they actually cover all the business processes associated with it. The monitoring of goals and the optimization of transactions becomes possible as future trends also become predictable. The real-time progress of an organization can be viewed via the generation of real-time report. These are also part of the software package. One advantage of data integration via a business intelligence software package is that 'organization-wide data coordination’ becomes possible. TIMELY ANALYSIS Shortened time durations spent in the analysis of massive amounts of data and also for predictive analysis is the second trend. Complex Event Processing algorithms are the newest technological advancement that enables the quick making of decisions. DATA GOVERNANCE The third trend is the capturing of accurate data via data governance. For business intelligence to get implemented successfully it is essential that the data being used for organizational implementation is accurate. INTEGRATION Coherent and combined processing between data warehousing and operating systems is proposed to take place. Traditional and automatic decision making is to be assisted by this integration. OFFICE AUTOMATION SYSTEMS External and internal users would both extensively use analytical software like Excel for conducting personal analysis and for varying amounts of data. New analytic and charting options in the software assist in the conduction of this analysis. DATA WAREHOUSING With the evolution of business processes and also with the continuously evolving business requirements the priorities for data warehousing are continuously on a rise. Integration of data is essential such that it can be readily available for instant retrieval, business processing and then embedding back into the business application. DATA VIRTUALIZATION Via Master Data Management or MDM varying ends of information can be integrated into one platform. INTRODUCTION OF SEMANTIC TECHNOLOGIES The structuring of unstructured data results in its efficient handling. The Advanced classification of data along with its filtering and content monitoring allows the increase of usability of data within the organization. PERFORMANCE MANAGEMENT AND RISK ANALYSIS In spite of the fact that in the current organizational set up process management and risk analysis holds separate ways they are proposed to be integrated into a single business process for future business intelligence implementations. This would ensure government compliance and financial performance. OPEN SOURCE And last but not the least. With users world over becoming increasingly aware of their business requirements and computerized information handling the latest development on the rise is the introduction of open source business intelligence software. The cost effectiveness of these systems is high along with their co-operation and combined execution with other closed source applications. The over all scenario governing the trends in business analysis are those that focus data integration, cost effective organizational solutions and predictive analysis just to name a few. SAP AND BUSINESS INTELLIGENCE SAP is extensive Business intelligence software that enables successful embedding of business intelligence issues within an organizational setup. SAP products are renowned for working together with customers in an easy and flexible fashion. Customer services have also always been the top most priority of SAP Business solution providers.  SAP NetWeaver Business intelligence With a specific focus on transactional data the SAP NetWeaver BI works to extract data from every possible source in order to clean, organize and normalize it. This is done to make the diversified data usable in a collective manner. The method is similar to SAP NetWeaver MDM with a difference of focus on transactional data only. The data from every business activity goes into the main data warehouse that is being controlled by the SAP Netweaver BI, the data warehouse at the core. Some of the features of SAP NetWeaver BI are highlighted in the text below. Core Functions: EDW (Enterprise data warehousing) This function of SAP NetWeaver BI enables the operators to create customized data ware house and to operate it in convenient and flexible manner. The notable features are, The integration of diverse systems. Support of different topologies. Development of topologies. Easy information access through layered methodology. Physical and virtual data Integration facility with real time access. Support for operational reporting and strategic analyses. The two IT scenario variants of Enterprise Data Warehousing are, Scenario variant for design time. Scenario variant for runtime. The variant for design time addresses the issues of modeling and implementation. The functions include, Data Modeling Source Definition Data distribution transformation Facilitation of meta data management. The run-time scenario variant is responsible for monitoring and administration issues. The functions include, Control of data flow. Performance optimization using performance analytics. Monitoring and administration. Management of information life cycle. User management facility. These two scenarios enable the user to design highly reliable, robust, scalable and flexible BI solution. INFORMATION HANDLING PROCESSES All the processes that involve the transfer of information such as querying, processing, handling and analysis etc. in order to serve the business needs within an enterprise have been taken care of. All the information that is handled when a user queries, generates reports or conducts analysis is handled by this enterprise edition. The querying and handling is considered at both design time and run time perspectives. Different options in the Business Explorer (BEx) suite encompassing a host of variants enable the definition, embedding, deployment, interaction with the SAP NetWeaver BI Data. ANALYSIS AND BUSINESS PLANNING The strategic and operational Planning requirements of an organization are well handled by SAP NetWeaver BI. An optimal combination of planning and analysis capabilities is intended. There are a number of capabilities that result in the eventual planning of the business processes. These include capabilities from the mere data entry options into the SAP Business Warehouse to the classification of this data for each of the business processes involved such as CRM etc. DATA QUALITY ASSURANCE Business Intelligence application with SAP ensures that accurate information reaches each business process. This, in turn, ensures the success of all the analysis that would then be conducted on the provided data. SAP NetWeaver BI possesses the ability to process and find out any mistakes in both raw data and transactional data. With ever growing everyday advancements In technology resulting in variations of data inputs such as “radio frequency identification”, ever growing query inputs by continuously engaging number of users and the gradually enhancing speed and reliability requirements from a business environment, SAP’s NetWeaver BI is expected to be acting as a system that empowers composite applications. SAP NetWeaver BI Accelerator The technology to reduce the query time of SAP NetWeaver BI is termed as Accelerator. It uses Blade Servers based scalable architecture. The accelerator speeds up the query retrieval time by making use of parallel processing, indexing and compression. The rate, to which the latency is reduced, is from 10 to 100 percent which is highly considerable difference. Figure 1 highlights the functioning and architecture of BI Accelerator. The effectiveness of accelerator requires heavy computation. Arrays and clusters of blade servers are used for this purpose. The accelerator achieves results through indexing distributed computing using the cache spread over the array of servers. The compressed data is first stored in the memory by going through the process of column based indexing. The indexed data is further stored in the array of cache enabling speedy search. All of the functioning remains invisible to the users through a layer of abstraction created by incorporating ‘easy to use’ and simple interfaces. Information cubes are constructed through normal query process and there is no need to incorporate specialized queries. The accelerator saves a lot of internal design tasks that may be incorporated for faster queries but are cumbersome and time taking. Figure 1. The SAP NetWeaver BI Accelerator. (Source: CodeIdol, 2009) SAP NETWEAVER BI and EMBEDDING OF ANALYTICS The most imposing impact that SAP net weaver BI has on the organizational setup is through the embedding of analysis. The first instance of SAP BI applications that is introduced into the market and is ‘Analytics Specific’ is named as “SAP xApp Analytics”. The concept behind embedded analytics that this issue offers is that the handling of raw data such that it reaches its specific destinations, gets analysis done on it and the results of the analysis get implemented back into the applications concerned. CONCLUSION: In line with the above discussion it can very well be ascertained that it is not long before business intelligence would not need to be embedded into each business environment rather it would itself be an integral business process itself. BI or Business Intelligence is a process that enables the successful execution of business processes within an organization. This is done by computerized handling and analysis of data in line with an organization’s knowledge management setup. REFERENCES: American Marketing Association AMA. (2011). Introduction to Marketing Research. [Online] Available at < http://www.marketingteacher.com/lesson-store/lesson-marketing-research.html.> [Accessed 15 August 2011] Centre for Advanced Analysis and Business Studies. (2011) Differences Between Knowledge management and Business Intelligence. [Online]. Available at [Accessed 3 August 2011] CodeIdol. (2009). SAP NetWeaver Business Intelligence. [Online] Available at[Accessed 15 August 2011] Csumb. (2011). Business Intelligence. [Online] Available at < it.csumb.edu/departments/data/glossary.html> [Accessed 17 August 2011] Kahn, B. K., Adams, E. M. Kenneth (2001) Sales forecasting as a knowledge management process. The Journal of Business Forecasting, [Online] Available at http://bus.utk.edu/ivc/forecasting/articles/Sales_Forecasting_as_a_Know ledge_Management_Process.pdf> [Accessed 15 August 2011] Sauder. (2011). Business Intelligence. [Online] Available at < www.sauder.ubc.ca/cgs/itm/itm_glossary.html> [Accessed 19 August 2011] Read More