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Business intelligence is the process of gathering information in the field of business. Information is typically obtained about customer needs, customer decision making processes, the competition, conditions in the industry, and general economic, technological, and cultural trends. Business intelligence is carried out to gain sustainable competitive advantage, and is a valuable core competence in some instances. Every business intelligence system has a specific goal, which is derived from an organisational goal or from the Vision statement. Goals could be short term (e.g.: quarterly numbers to Wall Street) or long term (shareholder value, target industry share / size etc).The term was first used by Gartner and popularized by analyst Howard Dresner. It describes the process of turning data into information and then into knowledge. The intelligence is claimed to be more useful to the user as it passes through each step.
Industrial espionage is a type of business intelligence that uses covert techniques. There is a grey area between "normal" business intelligence and industrial espionage.
Business performance management is a software oriented business intelligence system that some see as the new generation of business intelligence though the terms are used interchangeably by most in the industry.
The first probable reference to Business intelligence is made in Sun Tzu's "Art of War" where he claims that to succeed in war, you should have full knowledge of your strengths/weaknesses and full knowledge of your enemy's strengths/weaknesses. Lack of either one might result in defeat. BI is the art or wading through tons of data overload, sieving through data and presenting information - both internal (from operational systems) and external (market intelligence) - on which management can act or build strategies.
1 Some of the definitions of this field
- Systems that provide directed background data and reporting tools to support and improve the decision-making process.
- Business Intelligence provides business roadmaps to deliver solutions for business analysis which includes data models, meta-data and analytical applications. By having these roadmaps, we deliver superior business value through improved return on investment, time value by enabling fast solution delivery, and technical value through open database enablement.
- A term which represents those systems that help companies understand what makes the wheels of the corporation turn and to help predict the future impact of current decisions. These systems play a key role in strategic planning process of the corporation. Systems that exemplify business intelligence include medical research, customer profiling, market basket analysis, customer contact analysis, market segmentation, scoring, product profitability, and inventory movement.
- An interactive process of analyzing and exploring structured, domain-specific information (often stored in a data warehouse) to discern trends or patterns, thereby deriving insights and drawing conclusions. The BI process includes communicating findings and effecting change. BI domains include customers, products, services or competitors.
- Business intelligence (BI) is a broad category of applications and technologies for gathering, storing, analyzing, and providing access to data to help enterprise users make better business decisions.
- Usage of timely and accurate information to base decisions upon. Typically, includes a broad category of applications and technologies for gathering, storing, analyzing, and providing access to data. Activities include decision support, query and reporting, online analytical processing, statistical analysis, forecasting, and data mining.
2 Metrics /Key Performance Indicators
Most of the time, BI simply means use of several Financial/Nonfinancial Metrics/ Key Performance Indicators to assess the present state of business and to prescribe course of action. The key aspects of this are:
- Having a Process
- Having clear goals / performance requirements of the process
- Having a quantitative / qualitative measurement of the results and comparison with set goals
- Investigating variances and tweaking processes or resources to achieve long-term goals
Some of the areas which top management analyse could be -->
- Customer related numbers:
- New Customers Acquired
- Status of existing customers
- Attrition of Customers
- Turnover generated by segments of the Customers - these could be demographic filters.
- Outstanding balances held by segments of customers and terms of payment - these could be demographic filters.
- Collection of bad debts within Customer relationships.
- Demographic analysis of Individuals (potential customers) applying to become customers, and the levels of approval, rejections and pending numbers.
- Delinquency analysis of customers behind on payments.
- Profitability of customers by demographic segments and segmentation of customers by profitability.
This is more an inclusive list than an exclusive one. The above more or less describes what a bank would do, but could also refer to a Telephone company or similar service sector company.
What is important is:
- KPI-related data which is consistent and correct.
- Timely availability of KPI related Data.
More and more organisations are moving towards faster availability of data. Previously data usually was available only after a month or two, which might not be the best idea if you want to hit Wall street targets. Of late, several banks have tried to move from availability of data at shorter intervals and lesser delays. For Example, in businesses which have higher operational/credit risk loading (e.g.: Credit cards, Wealth management), Citibank has moved onto a weekly availability of KPI related data or sometimes a daily analysis of numbers. This means that data should usually be available within 24 hours at most times, necessicitating automation and the use of IT systems to achieve this.
