Types of Information Systems

Types of Information Systems

As discussed already, an information system is a collection of hardware, software, data, people and procedures that are designed to generate information that supports the day-to-day, short-range, and long-range activities of users in an organization.         

Information systems generally are classified into five categories office information systems, transaction processing systems, management information systems, decision support systems, and expert systems. The following sections present each of these information systems.

1. Office Information Systems (OIS)

An office information system is an information system that uses hardware, software and networks to enhance work flow and facilitate communications among employees. Win an office information system, also described as office automation; employees perform tasks electronically using computers and other electronic devices, instead of manually. With an office information system, for example, a registration department might post

the class schedule on the Internet and e-mail students when the schedule is updated. In a manual system, the registration department would photocopy the schedule and mail it to each student’s house.

An office information system supports a range of business office activities such as creating and distributing graphics and/or documents, sending messages, scheduling, and accounting. All levels of users from executive management to non-management employees utilize and benefit from the features of an OIS.

The software an office information system uses to support these activities include word processing, spreadsheets, databases, presentation graphics, e-mail, Web browsers, Web page authoring, personal information management, and groupware. Office information systems use communications technology such as voice mail, facsimile (fax), videoconferencing, and electronic data interchange (EDI) for the electronic exchange of text, graphics, audio, and video. An office information system also uses a variety of hardware, including computers equipped with modems, video cameras, speakers, and microphones; scanners; and fax machines.

2. Transaction Processing Systems (TPS)

A transaction processing system is an information system that captures and processes data generated during an organization’s day-to-day transactions. A transaction is a business activity such as a deposit, payment, order or reservation.

Clerical staff typically performs the activities associated with transaction processing, which include the following

Recording a business activity such as a student’s registration, a customer order, an employee’s timecard or a client’s payment.

Confirming an action or triggering a response, such as printing a student’s schedule, sending a thank-you note to a customer, generating an employee’s paycheck or issuing a receipt to a client.

Maintaining data, which involves adding new data, changing existing data, or removing unwanted data.

Transaction processing systems (TPS) were among the first computerized systems developed to process business data – a function originally called data processing. Usually,

the TPS computerized an existing manual system to allow for faster processing, reduced clerical costs and improved customer service.

The first transaction processing systems usually used batch processing. With batch processing, transaction data is collected over a period of time and all transactions are processed later, as a group. As computers became more powerful, system developers built online transaction processing systems. With online transaction processing (OLTP) the computer processes transactions as they are entered.

Today, most transaction processing systems use online transaction processing. Some routine processing tasks such as calculating paychecks or printing invoices, however, are performed more effectively on a batch basis. For these activities, many organizations still use batch processing techniques.

3. Management Information Systems (MIS)

While computers were ideal for routine transaction processing, managers soon realized that the computers’ capability of performing rapid calculations and data comparisons could produce meaningful information for management.

Management information systems thus evolved out of transaction processing systems. They generate accurate, timely and organized information so managers and other users can make decisions, solve problems, supervise activities, and track progress. Because it generates reports on a regular basis, a management information system sometimes is called a management reporting system (MRS)

Management information systems often are integrated with transaction processing systems. To process a sales order, for example, the transaction processing system records the sale, updates the customer’s account balance, and makes a deduction from inventory.

Using this information, the related management information system can produce reports that recap daily sales activities; list customers with past due account balances; graph slow or fast selling products; and highlight inventory items that need reordering. A management information system focuses on generating information that management and other users need to perform their jobs.

An MIS generates three basic types of information detailed, summary and exception. Detailed information typically confirms transaction processing activities. A

Detailed Order Report is an example of a detail report. Summary information consolidates data into a format that an individual can review quickly and easily. To help synopsize information, a summary report typically contains totals, tables, or graphs. An Inventory Summary Report is an example of a summary report.

Exception information filters data to report information that is outside of a normal condition. These conditions, called the exception criteria, define the range of what is considered normal activity or status. An example of an exception report is an Inventory Exception Report that notifies the purchasing department of items it needs to reorder. Exception reports help managers save time because they do not have to search through a detailed report for exceptions. Instead, an exception report brings exceptions to the manager’s attention in an easily identifiable form. Exception reports thus help them focus on situations that require immediate decisions or actions.

4. Decision Support Systems (DSS)

A decision support system is an information system designed to help users reach a decision when a decision-making situation arises. A variety of DSSs exist to help with a range of decisions as shown in Figure

Transaction processing and management information systems provide information on a regular basis. Frequently, however, users need information not provided in these reports to help them make decisions. A sales manager, for example, might need to determine how high to set yearly sales quotas based on increased sales and lowered product costs. Decision support systems help provide information to support such decisions.

A decision support system uses data from internal and/or external sources. Internal sources of data might include sales, manufacturing, inventory, or financial data from an organization’s database. Data from external sources could include interest rates, population trends, and costs of new housing construction or raw material pricing. Users of a DSS, often managers, can manipulate the data used in the DSS to help with decisions.

Some decision support systems include query language, statistical analysis capabilities, spreadsheets, and graphics that help you extract data and evaluate the results. Some decision support systems also include capabilities that allow to create a model of the factors affecting a decision. A simple model for determining the best product price, for example, would include factors for the expected sales volume at each price level. With the model, one can ask what-if questions by changing one or more of the factors and viewing the projected results. Many people use application software packages to perform DSS functions.

A special type of DSS, called an executive information system (EIS), is designed to support the information needs of executive management. Information in an EIS is presented in charts and tables that show trends, ratios, and other managerial statistics.

Because executives usually focus on strategic issues, EISs rely on external data sources such as the Internet. These external data sources can provide current information on interest rates, commodity prices, and other leading economic indicators.

To store all the necessary decision-making data, DSSs or EISs often use extremely large databases, called data warehouses. A data warehouse stores and manages the data required to analyze historical and current business circumstances.

5. Expert Systems

An expert system is an information system that captures and stores the knowledge of human experts and then imitates human reasoning and decision- making processes for those who have less expertise. Expert systems are composed of two main components a

knowledge base and inference rules. A knowledge base is the combined subject knowledge and experiences of the human experts.

The inference rules are a set of logical judgments applied to the knowledge base each time a user describes a situation to the expert system. Integrated Information Systems With today’s sophisticated hardware, software and communications technologies, it is often difficult to classify a system as belonging uniquely to one of the five information system types discussed. Much of today’s application software supports transaction processing and generates management information. Other applications provide transaction processing, management information, and decision support. Although expert systems still operate primarily as separate systems, organizations increasingly are consolidating their information needs into a single, integrated information system.

The key to gaining strategic advantages from IT lies in understanding the process of installing, implementing, adapting and managing a strategic information system. But there is growing literature and many case studies on why companies fail to strategically manage their information technology. Two main streams have emerged. The first suggests that top managers misunderstand IT and its strategic significance, mainly through neglect, fear of new technologies, and the wide spread practice of delegating unpleasant tasks. Prescriptions abound. Some suggest that a well-managed company will also generate strategic management of IT. Others have surveyed senior managers and found little enthusiasm for computers and other recent technologies on their desks, or in their decision processes. Hence, they recommend improved communications with the automation specialists in the company - to enhance learning and to allay managers’ inherent discomforts.

The second stream encompasses managerial systems tailored to the perceived tasks and needs of senior executives. Such systems include all “executive” brands of information systems, expert systems and decision support systems. The main idea is to enroll the best available and most recent automation technology in the service of the executive’s key functions, such as decision making. The results of these prescriptions and “support” systems are added confusion and an even stronger resistance on the part of senior managers to engage IT for strategic purposes.

The problem is essentially in the process, not solely in the perspective of senior management nor in their ability or inability to cope with recent technology. The advent of a new generation of senior managers better skilled in current technology by no means assures an improved strategic approach to IT and MIS. Senior managers make basic

decisions which determine, first, what the strategically and competitively important information systems are for the company. Thus, they set the overall direction and the key criteria for the acquisition of information systems and information technology.

Second, senior managers decide on the specific objectives of any given system (usually per recommendations of the systems professionals in the MIS function). Once this is established, the organizational factors, the systems design, and the technological choices will follow and most probably will be delegated to lower echelons and to varied functions in the company. However, although senior managers have had a key role in determining the information systems to be selected, purchased and established in the firm, their impact on the subsequent process of managing the routine operations of the systems is greatly diminished.

IT is essentially managed by the information systems professionals in the company. Further, IT is embedded in almost all functions and activities of the corporation, dispersed and diluted at all levels and departments. In addition, benefits accrued to the company from the usage of IT manifest themselves in improvements in the information system of the corporation and in its MIS, and are not directly measurable at the corporate/strategic level.

Therefore, to strategically manage IT, senior managers need to understand the diffusion of the technology and its role in information gathering, processing, and transfer at all levels and through the services of IS/MIS. Information technology is too important to be left to the sole discretion of information professionals.

In the field of business decision support, more and more recent research has been concentrating on the human side of the person-technology relation in decision making. It has been shown in a variety of works that business decision making environment is a unity of decision makers’ experience, beliefs and perceptions on one side, and decision support tools and techniques – on the other side.

The information environment surrounding business activities and decisions is getting increasingly complex due to growing volumes of information of potential relevance to certain business activities; increasing number of sources of such information; and multiplying technologies for accessing and handling data and information. The expected role of information technologies (IT) is to filter and direct relevant information flows and to provide reliable and flexible support.

At the same time, every case of decision making for a problem situation tests the existing support mechanisms and provides valuable information for future situations, thus creating new knowledge and experience for participants involved, and in the case of right decision increasing confidence in future actions.

Summing up recent research work on the human side of IT management decision support, there seems to be agreement that IT should act as

An enhancing instrument for decision search and analysis as a high-level and knowledge-intensive management activities,

A creativity stimulation and managerial learning tool,

An instrument for reduction of biased attitudes as well as insurance from making fatal decisions,

An instrument for maintaining, managing and developing the explicit part of knowledge on decision making – models, situations, scenarios, case studies etc.

These guidelines have served as a basis for conducting the interviews whose results are presented further.

Decision-Making Environment

In making important decisions, any information sources that contain relevant important information are going to be accessed and used, if possible. As pointed out in, the decision maker uses the whole network of information sources and variety of available media.

In most cases it is impossible to access or produce all required information, so decisions are made under circumstances of uncertainty and incomplete information. Business decision support seems to have common ground with other areas containing significant analytical work scientific research, military and political intelligence, or criminal investigation– in all cases, there are

A problem situation which requires analysis in line with general strategy and goals. Assumptions,

Deficit of information (and time in many cases), and

Certain (usually big) amounts of diverse empiric data which is chaotic in its nature

Has to be processed in some way for relevant facts and findings Field knowledge is required to extract these facts and findings,

The calculated facts and findings are carefully evaluated against wider context - Political, social, ethical etc.

Growing IT support.

Apart from needs for data and information and their availability, knowledge possessed or required by the decision making subject is an important part of the decision environment.

The most common understanding of relations between data, information and knowledge is Data → Information → Knowledge. In other words, data is processed into information, which is evaluated against existing knowledge or stimulates creation of new knowledge in a sense that missing links in the decision model are produced and put in place.

There is existing recent research suggesting looking at other relations or sequence chains between data, information and knowledge with the idea that better understanding of these sequences might help producing better support for problem situations. A few examples

Knowledge → Information → Data

This sequence might be based on having the knowledge to look for information and then turn it into data. For instance, in a problem situation general and professional knowledge can point to what information is needed to make the right decision, what information is readily available, and what information must be produced from some sources. This information is then worked into decision data – prices to be set, planned investment, resource distribution and redistribution, budget structure and so on.

Data → Knowledge → Information

Knowledge is required to process data into information. Another possible case the content of data suggests ways (or produces new knowledge) to extract information out of this data, e.g., group or query the data by some criteria which carry business logic or other rationale.

Information → Knowledge → Data

Knowledge is required to get data from information, where data amounts to final decision criteria buy – don’t buy; accept proposal – reject proposal; set the price etc.

From the need for simple outcome the situation can be worked backwards to track what information would be needed to, for instance, estimate the price, and what knowledge precedes the definition of this information, its sources, completeness, Such decision disassembly might help to explain better what exactly should be supported and how to do it best.

Knowledge → Data → Information

Probably this path is possible only conditionally if we admit that having knowledge we know where to look for data to produce required information.

Information → Data → Knowledge

The final phase of a decision where decision information is processed and discussed into a decision which might be in a form of data – a simple figure, a set of figures, text, choice, but it carries the load of preceding decision information, concepts and models, and its emergence leads to new knowledge added to existing body.

To clarify the issues of management decision support in the two dimensions of “how much coverage” (that is, how many decision support functions and activities use or benefit from IT), and “in what way” (the actual manner of use, as compared to the research forecasts), the following topics are to be considered

Attributes of actual good or well-prepared decision,

Attributes of actual wrong decisions,

Role of information sources for the above,

Role of analytical tools for the above,

Issues that stimulate creative thinking,

Role of IT in decision making,

Decision maker’s idea of an ideal environment for decision making.

On the attributes of actual good or well-prepared decision, the issues are

Key factual information presented or available (This information has to possess the features attributed to user quality timely and current, correct, complete, relevant, accurate, easy to use etc.),

‘Soft’ information available and utilized for clear understanding of the present and future environment. The most important points regarding ‘soft’ information can be summarized as

Filtering

Filtering the decision maker selects the most important and reliable information of this type;

Transformation

Transformation the decision maker transforms soft information into hard data and rules by own judgment, or by the existing rules (e.g., laws and other legal acts which can govern translation of “soft” information into “hard” data);

Integration

Integration the decision maker compares one available information against other, looking for matching pieces, confirmations or denials;

Testing

Testing received “soft” information helps to challenge formal information or come back to the formal model with new assumptions;

Stimulation

Stimulation received “soft” information may stimulate Clear alternatives.

Analytical tools have capabilities of different scenarios or “what-if” analysis. Here “analytical tools” have meant any formal methods, approaches, models and their software, if used, to be applied to solve a decision problem.

Existence of an analytical tool that is problem- specific or suitable for the required kind of problem; also its ‘reputation’, meaning that this tool has been used and accepted by solvers of similar problems;

Convenience of use, when an analytical tool can be used without specific training or considerable consulting services;

Clear relations between data describing the problem situation;

Ability to reduce information chaos to a manageable set of key data or introduce required relations between data in problem environment.

Attributes of actual wrong decisions include

Too much of self-confidence, which can be translated into conscious use of limited problem model, and

Serious external factors omitted such as

Low quality advice from outside advisers;

Wrong “soft” information which was supposed to be trusted;

Mis-formulated problem – a symptom mistaken for a problem;

Not using information, tacit and explicit, to make an informed decision.

The named factors of wrong decisions might be grouped into two general groups

Information Factors

Lack or misuse of important information about the problem situation; Political Factors

Override of formal reasoning by power. Here, it has to be noted that the political factors are assumed to be as well based on some specific information available to deciding authority, but most often unavailable to the participants involved in the formal reasoning.

Role of information sources for both right and wrong decisions has drawn quite uniform responses from the responders in stating that information sources, their variety, quality and ease of access is most important for producing quality decisions. Regarding

the role of IT, the importance of internal and external IT- supported sources (own, public and commercial databases, Internet etc.) has been facilitated by improving user interfaces and convenient mechanisms for information search and querying.

The important point here is that growth of information volumes available does not go in hand with the growth of quality sources, and it does not necessarily lead to the growth of the body of knowledge. Decisions also have been influenced by the mechanisms for information and knowledge sharing, and for capturing experiences.

Role of analytical tools (modeling software packages and functions) has been indi-cated as being minor to moderate. This attitude can be attributed to the following factors

Problem-specific nature of the analytical tools; decision making style based on the use of

Decision information in its initial, unprocessed form; quite often for a decision-making entity the sheer availability of the relevant facts and figures having undergone simple, if none, processing and aggregation is considered sufficient.

Factors Stimulating Creative Thinking

Although widely regarded as one of the key ingredients for making a right decision in an unstructured situation, creativity has been one of the most difficult things to talk about. Generally, “creativity” has been regarded by most as an approach which allows them to find alternatives or courses of action that are outside conventional reasoning for a certain situation.

The factors that stimulate creativity in decision making can be grouped into three groups described below.

Independent view,

Decision manipulation tools and techniques, and

Underlying environment

Conclusions

The role of IT draws a slightly controversial impression at first sight – the confidence and expectations are high, and the actual usage at the same time is somewhat reserved. Eventually, the conclusion is that decision makers prefer simple and trusted

tools and techniques to achieve more with less – the job of the technology is to provide guiding and informing points to stimulate the decision makers’ concentration instead of interfering with it.

IT is recognized to be helpful in basic tasks – organizing and managing data and information, querying databases, sharing and propagating information, manipulating flexible models, presenting information in a convincing manner. Regarding the simple support tools and techniques, and decision makers’ ideas on the ideal decision environment, a concept of “information control center” can be developed for a decision making environment, where the key information sources and most often used support tools are always up and accessible just by few mouse clicks.

The possibilities of IT in facilitating problem solving creativity are an important issue in itself; here the technology has some proven points – idea generation, exchange and testing mechanisms; growing sophistication of work styles; support of teamwork and communication.