Business intelligence

Business intelligence (BI) is a business management term, which refers to applications and technologies that are used to gather, provide access to, and analyze data and information about company operations. Business intelligence systems can help companies have a more comprehensive knowledge of the factors affecting their business, such as metrics on sales, production, internal operations, and they can help companies to make better business decisions.

Rationale for using BI

Business Intelligence applications and technologies can enable organizations to make more informed business decisions, and they may give a company a competitive advantage. For example, a company could use business intelligence applications or technologies to extrapolate information from indicators in the external environment and forecast the future trends in their sector. Business intelligence is used to improve the timeliness and quality of information and enable managers to better understand the position of their firm in comparison to its competitors.

Business Intelligence applications and technologies can help companies analyze the following: changing trends in market share, changes in customer behavior and spending patterns, customers' preferences, company capabilities and market conditions. Business intelligence can be used to help analysts and managers determine which adjustments are most likely to affect trends.

BI systems can also be designed to provide managers with information on the state of economic trends or marketplace factors, or to provide managers with in depth knowledge about the internal operations of a business.

BI Technologies
For the BI (Business Intelligence) technology system to work effectively, companies address the need to have a secure computer system which can specify different levels of user access to the data 'warehouse', depending on whether the user is a junior staffer, manager, or executive. As well, a BI system needs to have sufficient data capacity, a plan for how long data will be stored (data retention). Analysts also need to set benchmark and performance targets for the system.
Business intelligence analysts have developed software tools to gather and analyze large quantities of unstructured data, such as production metrics, sales statistics, attendance reports, and customer attrition figures. Each BI vendor typically develops Business Intelligence systems differently, to suit the demands of different sectors (e.g., retail companies, financial services companies, etc.).

Business intelligence software and applications includes a range of tools. Some BI applications are used to analyze performance, projects, or internal operations, such as:

• AQL - Associative Query Logic;
• Scorecarding;
• Business activity monitoring;
• Business Performance Management and Performance Measurement;
• Business Planning;
• Business Process Re-engineering;
• Competitive Analysis;
• User/End-user Query and Reporting;
• Enterprise Management systems;
• Executive Information Systems (EIS);
• Supply Chain Management/Demand Chain Management;
• Finance and Budgeting tools.

Other BI applications are used to store and analyze data, such as:

• Data mining (DM),
• Data Farming,
• Data warehouses;
• Decision Support Systems (DSS) and Forecasting;
• Document warehouses
• Document Management;
• Knowledge Management;
• Mapping,
• Information visualization,
• Dashboarding;
• Management Information Systems (MIS);
• Geographic Information Systems (GIS);
• Trend Analysis;
• Software as a service (SaaS) Business Intelligence offerings (On Demand);
• Online analytical processing (OLAP)
• Real time business intelligence;
• Statistics and Technical Data Analysis;
• Web Mining, Text mining
• Systems intelligence.

Other BI applications are used to analyze or manage the "human" side of businesses, such as Customer Relationship Management (CRM) and Marketing tools and Human Resources applications.Web Personalization For examples of implemented Business Intelligence systems, see the BI screenshot collection at The Dashboard Spy


Key Intelligence Topics
Business intelligence often uses key performance indicators (KPIs) to assess the present state of business and to prescribe a course of action. Prior to the widespread adoption of computer and web applications, when information had to be manually inputted and calculated, performance data was often not available for weeks or months. Recently, banks have tried to make data available at shorter intervals and have reduced delays. The KPI methodology was further expanded with the Chief Performance Officer methodology which incorporated KPIs and root cause analysis into a single methodology.

Businesses that face higher operational/credit risk loading, such as credit card companies and "wealth management" services often make KPI-related data available weekly. In some cases, companies may even offer a daily analysis of data. This fast pace requires analysts to use IT systems to process this large volume of data.

Designing and implementing a business intelligence program
When implementing a BI programme one might like to pose a number of questions and take a number of resultant decisions, such as:

• Goal Alignment queries: The first step determines the short and medium-term purposes of the programme. What strategic goal(s) of the organization will the programme address? What organizational mission/vision does it relate to? A crafted hypothesis needs to detail how this initiative will eventually improve results / performance (i.e. a strategy map).
• Baseline queries: Current information-gathering competency needs assessing. Does the organization have the capability of monitoring important sources of information? What data does the organization collect and how does it store that data? What are the statistical parameters of these data, e.g. how much random variation does it contain? Does the organization measure this?
• Cost and risk queries: The financial consequences of a new BI initiative should be estimated. It is necessary to assess the cost of the present operations and the increase in costs associated with the BI initiative? What is the risk that the initiative will fail? This risk assessment should be converted into a financial metric and included in the planning.
• Customer and Stakeholder queries: Determine who will benefit from the initiative and who will pay. Who has a stake in the current procedure? What kinds of customers/stakeholders will benefit directly from this initiative? Who will benefit indirectly? What are the quantitative / qualitative benefits? Is the specified initiative the best way to increase satisfaction for all kinds of customers, or is there a better way? How will customers' benefits be monitored? What about employees,… shareholders,… distribution channel members?
• Metrics-related queries: These information requirements must be operationalized into clearly defined metrics. One must decide what metrics to use for each piece of information being gathered. Are these the best metrics? How do we know that? How many metrics need to be tracked? If this is a large number (it usually is), what kind of system can be used to track them? Are the metrics standardized, so they can be benchmarked against performance in other organizations? What are the industry standard metrics available?
• Measurement Methodology-related queries: One should establish a methodology or a procedure to determine the best (or acceptable) way of measuring the required metrics. What methods will be used, and how frequently will the organization collect data? Do industry standards exist for this? Is this the best way to do the measurements? How do we know that?
• Results-related queries: Someone should monitor the BI programme to ensure that objectives are being met. Adjustments in the programme may be necessary. The programme should be tested for accuracy, reliability, and validity. How can one demonstrate that the BI initiative (rather than other factors) contributed to a change in results? How much of the change was probably random?.