History

An early reference to non-business performance management occurs in Sun Tzu's The Art of War. Sun Tzu claims that to succeed in war, one should have full knowledge of one's own strengths and weaknesses and full knowledge of one's enemy's strengths and weaknesses. Lack of either one might result in defeat. A certain school of thought draws parallels between the challenges in business and those of war, specifically:

• collecting data - both internal and external
• discerning patterns and meaning in the data (analyzing)
• responding to the resultant information

Prior to the start of the Information Age in the late 20th century, businesses sometimes took the trouble to laboriously collect data from non-automated sources. As they lacked computing resources to properly analyze the data they often made commercial decisions primarily on the basis of intuition.

As businesses started automating more and more systems, more and more data became available. However, collection remained a challenge due to a lack of infrastructure for data exchange or due to incompatibilities between systems. Reports on the data gathered sometimes took months to generate. Such reports allowed informed long-term strategic decision-making. However, short-term tactical decision-making continued to rely on intuition.

In modern businesses, increasing standards, automation, and technologies have led to vast amounts of data becoming available. Data warehouse technologies have set up repositories to store this data. Improved ETL and even recently Enterprise Application Integration tools have increased the speedy collecting of data. OLAP reporting technologies have allowed faster generation of new reports which analyze the data. Business intelligence has now become the art of sieving through large amounts of data, extracting useful information and turning that information into actionable knowledge.

In 1989 Howard Dresner, a research analyst at Gartner , popularized "Business Intelligence" as an umbrella term to describe a set of concepts and methods to improve business decision-making by using fact-based support systems. Performance Management is built on a foundation of BI, but marries it to the planning and control cycle of the enterprise - with enterprise planning, consolidation and modeling capabilities.

Information technology management(or IT management)

is a combination of two branches of study, information technology and management.

Strictly speaking, there are two incarnations to this definition. One implies the management of a collection of systems, infrastructure, and information that resides on them. Another implies the management of information technologies as a business function.

The first definition stems from the practice of IT Portfolio Management and is the subject of technical manuals and publications of various information technologies providers; while the second definition stems from the discussion and formation of the Information Technology Infrastructure Library (ITIL).

The ITIL has been in practice throughout regions of the world mainly conducted by IT service providers consulting companies. The relative paucity in the use of the best practice set can be attributed to a lack of awareness among IT practitioners. However the lack of ready-to-use tools also presents a significant barrier.

Some organizations that value such practices tend to engage consultants to introduce the practice. Such implementations can conflict with the home-grown culture due to a lack of internal buy-in. Other organizations implement the practices by spending resources to develop in-house tools.

Most in-house developed tools tend to focus on one or a few specific areas where the orgnizations feel the most pains. To reap the full advantages, tools will need to be integrated with the organization's IT data in the center.

BI technologies

For a BI technology system to work effectively, a company should 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, a manager, or an executive. As well, a BI system should have sufficient data capacity and a plan for how long data will be stored (data retention). Analysts should 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 include 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, and Finance and Budgeting tools.

Other BI technologies are used to store and analyze data, such as Data mining (DM), Data Farming, and Data warehouses; Decision Support Systems (DSS) and Forecasting; Document warehouses and Document Management; Knowledge Management; Mapping, Information visualization, and Dashboarding; Management Information Systems (MIS); Geographic Information Systems (GIS); Trend Analysis; Software as a service (SaaS) Business Intelligence offerings (On Demand) — which is similar to traditional BI solutions, but software is hosted for customers by a provider^[3]; Online analytical processing (OLAP) and multidimensional analysis, sometimes called "Analytics" (based on the "hypercube" or "cube"); Real time business intelligence; Statistics and Technical Data Analysis; Web Mining; Text mining; and 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.

Definition

The terms MIS and information system are often confused. Information systems include systems that are not intended for decision making. MIS is sometimes referred to, in a restrictive sense, as information technology management. That area of study should not be confused with computer science. IT service management is a practitioner-focused discipline. MIS has also some differences with Enterprise Resource Planning (ERP) as ERP incorporates elements that are not necessarily focused on decision support.

Alan Lee defines MIS as "...research in the information systems field examines more than just the technological system, or just the social system, or even the two side by side; in addition, it investigates the phenomena that emerge when the two interact."

Background

In their infancy, business computers were used for the practical business of computing the payroll and keeping track of accounts payable and receivable. As applications were developed that provided managers with information about sales, inventories, and other data that would help in managing the enterprise, the term "MIS" arose to describe these kinds of applications. Today, the term is used broadly in a number of contexts and includes (but is not limited to): decision support systems, resource and people management applications, project management, and database retrieval applications.

Management Information Systems

Management Information Systems (MIS), sometimes referred to as Information Management and Systems, is the discipline covering the application of people, technologies, and procedures — collectively called information systems — to solving business problems. Management Information Systems are distinct from regular information systems in that they are used to analyze other information systems applied in operational activities in the organization.Academically, the term is commonly used to refer to the group of information management methods tied to the automation or support of human decision making, e.g. Decision Support Systems, Expert systems, and Executive information systems.