Management information system

Master of Business Administration

Semester II

MB0047 – Management Information Systems

Assignment

Set- 1

1. What is MIS? Define the characteristics of MIS? What are the basic Functions of MIS? Give some Disadvantage of MIS?

Ans.

A management information system (MIS) provides information which is needed to manage organizations efficiently and effectively. Management information systems involve three primary resources: people, technology, and information or decision making. Management information systems are distinct from other information systems in that they are used to analyze 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.

Overview

Initially in businesses and other organizations, internal reporting was produced manually and only periodically, as a by-product of the accounting system and with some additional statistic(s), and gave limited and delayed information on management performance. Data was organized manually according to the requirements and necessity of the organization. As computational technology developed, information began to be distinguished from data and systems were developed to produce and organize abstractions, summaries, relationships and generalizations based on the data.

Early business computers were used for simple operations such as tracking sales or payroll data, with little detail or structure. Over time, these computer applications became more complex, hardware storage capacities grew, and technologies improved for connecting previously isolated applications. As more and more data was stored and linked, managers sought greater detail as well as greater abstraction with the aim of creating entire management reports from the raw, stored data. The term "MIS" arose to describe such applications providing managers with information about sales, inventories, and other data that would help in managing

the enterprise. 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, enterprise resource planning (ERP), enterprise performance management (EPM), supply chain management (SCM), customer relationship management (CRM),project management and database retrieval applications.

The successful MIS supports a business's long range plans, providing reports based upon performance analysis in areas critical to those plans, with feedback loops that allow for titivation of every aspect of the enterprise, including recruitment and training regimens. MIS not only indicate how things are going, but why and where performance is failing to meet the plan. These reports include near-real-time performance of cost centers and projects with detail sufficient for individual accountability.

Types

Most management information systems specialize in particular commercial and industrial sectors, aspects of the enterprise, or management substructure.

Management information systems (MIS), per se, produce fixed, regularly scheduled reports based on data extracted and summarized from the firm’s underlying transaction processing systems to middle and operational level managers to identify and inform structured and semi-structured decision problems.

Decision support systems (DSS) are computer program applications used by middle management to compile information from a wide range of sources to support problem solving and decision making.

Executive information systems (EIS) is a reporting tool that provides quick access to summarized reports coming from all company levels and departments such as accounting, human resources and operations.

Marketing information systems are MIS designed specifically for managing the marketing aspects of the business.

Office automation systems (OAS) support communication and productivity in the enterprise by automating work flow and eliminating bottlenecks. OAS may be implemented at any and all levels of management.

School management information systems (MIS) cover school administration, often including teaching and learning materials.

Advantages

The following are some of the benefits that can be attained for different types of management information systems.

Companies are able to highlight their strengths and weaknesses due to the presence of revenue reports, employees' performance record etc. The identification of these aspects can help the company improve their business processes and operations.

Giving an overall picture of the company and acting as a communication and planning tool. The availability of the customer data and feedback can help the company to align their

business processes according to the needs of the customers. The effective management of customer data can help the company to perform direct marketing and promotion activities.

Information is considered to be an important asset for any company in the modern competitive world. The consumer buying trends and behaviours can be predicted by the analysis of sales and revenue reports from each operating region of the company.

Enterprise applications

Enterprise systems, also known as enterprise resource planning (ERP) systems provide an organization with integrated software modules and a unified database which enable efficient planning, managing, and controlling of all core business processes across multiple locations. Modules of ERP systems may include finance, accounting, marketing, human resources, production, inventory management and distribution.

Supply chain management (SCM) systems enable more efficient management of the supply chain by integrating the links in a supply chain. This may include suppliers, manufacturer, wholesalers, retailers and final customers.

Customer relationship management (CRM) systems help businesses manage relationships with potential and current customers and business partners across marketing, sales, and service.

Knowledge management system (KMS) helps organizations facilitate the collection, recording, organization, retrieval, and dissemination of knowledge. This may include documents, accounting records, and unrecorded procedures, practices and skills.

Developing Information Systems.

"The actions that are taken to create an information system that solves an organizational problem are called system development. These include system analysis, system design,programming/implementation, testing, conversion, production and finally maintenance. These actions usually take place in that specified order but some may need to repeat or be accomplished concurrently.

Conversion is the process of changing or converting the old system into the new. This can be done in four ways:

Direct cutover – The new system replaces the old at an appointed time. Pilot study – Introducing the new system to a small portion of the operation to see how it

fares. If good then the new system expands to the rest of the company. Phased approach – New system is introduced in stages.

2. Explain Knowledge based system? Explain DSS and OLAP with example?

Ans.

Knowledge-based systems

Knowledge based systems are artificial intelligent tools working in a narrow domain to provide intelligent decisions with justification. Knowledge is acquired and represented using various knowledge representation techniques rules, frames and scripts. The basic advantages offered by such system are documentation of knowledge, intelligent decision support, self learning, reasoning and explanation. Knowledge-based systems are systems based on the methods and techniques of Artificial Intelligence.

Their core components are:

knowledge base acquisition mechanisms inference mechanisms

Knowledge Base Systems (KBS) goes beyond the decision support philosophy to indicate the expert system technology into the decision making framework. Expert Systems (ES) have been the tools and techniques perfected by artificial intelligence (AI) researchers to deduce decision influences based on codification of knowledge. The codification of knowledge use the principles of knowledge representation (part of the large theoretical ideas of knowledge engineering). Typically such codification uses rules like IF-THEN rules to represent logical implications.

While for some authors expert systems, case-based reasoning systems and neural networks are all particular types of knowledge-based systems, there are others who consider that neural networks are different, and exclude it from this category.

KBS is a frequently used abbreviation for knowledge-based system.

Decision support system

A decision support system (DSS) is a computer-based information system that supports business or organizational decision-making activities. DSSs serve the management, operations, and planning levels of an organization and help to make decisions, which may be rapidly changing and not easily specified in advance.

DSSs include knowledge-based systems. A properly designed DSS is an interactive software-based system intended to help decision makers compile useful information from a combination of raw data, documents, personal knowledge, or business models to identify and solve problems and make decisions.

Typical information that a decision support application might gather and present are:

inventories of information assets (including legacy and relational data sources, cubes, data warehouses, and data marts),

comparative sales figures between one period and the next, projected revenue figures based on product sales assumptions.

Three fundamental components of a DSS architecture are:

1. the database (or knowledge base),2. the model (i.e., the decision context and user criteria), and3. the user interface.

The users themselves are also important components of the architecture.[5][12]

Applications

As mentioned above, there are theoretical possibilities of building such systems in any knowledge domain.

One example is the clinical decision support system for medical diagnosis. Other examples include a bank loan officer verifying the credit of a loan applicant or an engineering firm that has bids on several projects and wants to know if they can be competitive with their costs.

DSS is extensively used in business and management. Executive dashboard and other business performance software allow faster decision making, identification of negative trends, and better allocation of business resources.

A growing area of DSS application, concepts, principles, and techniques is in agricultural production, marketing for sustainable development. For example, the DSSAT4 package, developed through financial support of USAID during the 80's and 90's, has allowed rapid assessment of several agricultural production systems around the world to facilitate decision-making at the farm and policy levels. There are, however, many constraints to the successful adoption on DSS in agriculture.

DSS are also prevalent in forest management where the long planning time frame demands specific requirements. All aspects of Forest management, from log transportation, harvest scheduling to sustainability and ecosystem protection have been addressed by modern DSSs.

A specific example concerns the Canadian National Railway system, which tests its equipment on a regular basis using a decision support system. A problem faced by any railroad is worn-out or defective rails, which can result in hundreds of derailments per year. Under a DSS, CN managed to decrease the incidence of derailments at the same time other companies were experiencing an increase.

OLAP

An OLAP cube is a set of data, organized in a way that facilitates non-predetermined queries for aggregated information, or in other words, online analytical processing. OLAP is one of the computer-based techniques for analyzing business data that are collectively called business intelligence.

OLAP operations

The analyst can understand the meaning contained in the databases using multi-dimensional analysis. By aligning the data content with the analyst's mental model, the chances of confusion and erroneous interpretations are reduced. The analyst can navigate through the database and screen for a particular subset of the data, changing the data's orientations and defining analytical calculations. The user-initiated process of navigating by calling for page displays interactively, through the specification of slices via rotations and drill down/up is sometimes called "slice and dice". Common operations include slice and dice, drill down, roll up, and pivot.

3. What are Value Chain Analysis & describe its significance in MIS? Explain what is meant by BPR? What is its significance? How Data warehousing & Data Mining is useful in terms of MIS?

Ans.

Value chain

A value chain is a chain of activities for a firm operating in a specific industry. The business unit is the appropriate level for construction of a value chain, not the divisional level or corporate level. Products pass through all activities of the chain in order, and at each activity the product gains some value. The chain of activities gives the products more added value than the sum of the independent activities' values.

It is important not to mix the concept of the value chain with the costs occurring throughout the activities. A diamond cutter, as a profession, can be used to illustrate the difference of cost and the value chain. The cutting activity may have a low cost, but the activity adds much of the value to the end product, since a rough diamond is significantly less valuable than a cut diamond. Typically, the described value chain and the documentation of processes, assessment and auditing of adherence to the process routines are at the core of the quality certification of the business, e.g. ISO 9001.

Significance

The value chain framework quickly made its way to the forefront of management thought as a powerful analysis tool for strategic planning. The simpler concept of value streams, a cross-functional process which was developed over the next decade, had some success in the early 1990s.

The value-chain concept has been extended beyond individual firms. It can apply to whole supply chains and distribution networks. The delivery of a mix of products and services to the end customer will mobilize different economic factors, each managing its own value chain. The industry wide synchronized interactions of those local value chains create an extended value chain, sometimes global in extent. Porter terms this larger interconnected system of value chains the "value system." A value system includes the value chains of a firm's supplier (and their suppliers all the way back), the firm itself, the firm distribution channels, and the firm's buyers (and presumably extended to the buyers of their products, and so on).

Capturing the value generated along the chain is the new approach taken by many management strategists. For example, a manufacturer might require its parts suppliers to be located nearby its assembly plant to minimize the cost of transportation. By exploiting the upstream and downstream information flowing along the value chain, the firms may try to bypass the intermediaries creating new business models, or in other ways create improvements in its value system.

Value chain analysis has also been successfully used in large Petrochemical Plant Maintenance Organizations to show how Work Selection, Work Planning, Work Scheduling and finally Work

Execution can (when considered as elements of chains) help drive Lean approaches to Maintenance. The Maintenance Value Chain approach is particularly successful when used as a tool for helping Change Management as it is seen as more user friendly than other business process tools.

Value chain approach could also offer a meaningful alternative to valuate private or public companies when there is a lack of publically known data from direct competition, where the subject company is compared with, for example, a known downstream industry to have a good feel of its value by building useful correlations with its downstream companies.

Value chain analysis has also been employed in the development sector as a means of identifying poverty reduction strategies by upgrading along the value chain. Although commonly associated with export-oriented trade, development practitioners have begun to highlight the importance of developing national and intra-regional chains in addition to international ones.

Business process reengineering

Business process re-engineering is the analysis and design of workflows and processes within an organization. According to Davenport (1990) a business process is a set of logically related tasks performed to achieve a defined business outcome. Re-engineering is the basis for many recent developments in management. The cross-functional team, for example, has become popular because of the desire to re-engineer separate functional tasks into complete cross-functional processes. Also, many recent management information systems developments aim to integrate a wide number of business functions. Enterprise resource planning, supply chain management, knowledge management systems, groupware and collaborative systems, Human Resource Management Systems and customer relationship management.

Business process re-engineering is also known as business process redesign, business transformation, or business process change management.

Business Process Re-engineering (BPR) is basically the fundamental re-thinking and radical re-design, made to an organization's existing resources. It is more than just business improvising.

It is an approach for redesigning the way work is done to better support the organization's mission and reduce costs. Reengineering starts with a high-level assessment of the organization's mission, strategic goals, and customer needs. Basic questions are asked, such as "Does our mission need to be redefined? Are our strategic goals aligned with our mission? Who are our customers?" An organization may find that it is operating on questionable assumptions, particularly in terms of the wants and needs of its customers. Only after the organization rethinks what it should be doing, does it go on to decide how best to do it.

Within the framework of this basic assessment of mission and goals, re-engineering focuses on the organization's business processes—the steps and procedures that govern how resources are used to create products and services that meet the needs of particular customers or markets. As a structured ordering of work steps across time and place, a business process can be decomposed into specific activities, measured, modeled, and improved. It can also be completely redesigned or eliminated altogether. Re-engineering identifies, analyzes, and re-designs an organization's

core business processes with the aim of achieving dramatic improvements in critical performance measures, such as cost, quality, service, and speed.

Re-engineering recognizes that an organization's business processes are usually fragmented into sub processes and tasks that are carried out by several specialized functional areas within the organization. Often, no one is responsible for the overall performance of the entire process. Re-engineering maintains that optimizing the performance of sub processes can result in some benefits, but cannot yield dramatic improvements if the process itself is fundamentally inefficient and outmoded. For that reason, re-engineering focuses on re-designing the process as a whole in order to achieve the greatest possible benefits to the organization and their customers. This drive for realizing dramatic improvements by fundamentally re-thinking how the organization's work should be done distinguishes re-engineering from process improvement efforts that focus on functional or incremental improvement.

The role of information technology

Information technology (IT) has historically played an important role in the reengineering concept. It is considered by some as a major enabler for new forms of working and collaborating within an organization and across organizational borders.

Early BPR literature identified several so called disruptive technologies that were supposed to challenge traditional wisdom about how work should be performed.

Shared databases, making information available at many places Expert systems, allowing generalists to perform specialist tasks Telecommunication networks, allowing organizations to be centralized and decentralized at

the same time Decision-support tools, allowing decision-making to be a part of everybody's job Wireless data communication  and portable computers, allowing field personnel to work

office independent Interactive videodisk, to get in immediate contact with potential buyers Automatic identification and tracking, allowing things to tell where they are, instead of

requiring to be found High performance computing, allowing on-the-fly planning and revisioning

In the mid 1990s, especially workflow management systems were considered as a significant contributor to improved process efficiency. Also ERP (Enterprise Resource Planning) vendors, such as SAP, JD Edwards, Oracle, PeopleSoft, positioned their solutions as vehicles for business process redesign and improvement.

Benefiting from lessons learned from the early adopters, some BPR practitioners advocated a change in emphasis to a customer-centric, as opposed to an IT-centric, methodology. One such methodology, that also incorporated a Risk and Impact Assessment to account for the impact that BPR can have on jobs and operations, was described by Lon Roberts (1994). Roberts also stressed the use of change management tools to proactively address resistance to change—a

factor linked to the demise of many reengineering initiatives that looked good on the drawing board.

Some items to use on a process analysis checklist are: Reduce handoffs, Centralize data, Reduce delays, Free resources faster, Combine similar activities. Also within the management consulting industry, a significant number of methodological approaches have been developed.

Adequate IT Infrastructure Researchers consider adequate IT infrastructure reassessment and composition as a vital factor in successful BPR implementation (Al-Mashari & Zairi, 1999). Hammer (1990) prescribes the use of IT to challenge the assumptions inherent in the work process that have existed since long before the advent of modern computer and communications technology (Malhotra, 1998). Factors related to IT infrastructure have been increasingly considered by many researchers and practitioners as a vital component of successful BPR efforts (Ross, 1998). Effective alignment of IT infrastructure and BPR strategy, building an effective IT infrastructure, adequate IT infrastructure investment decision, adequate measurement of IT infrastructure effectiveness, proper information systems (IS) integration, effective reengineering of legacy IS, increasing IT function competency, and effective use of software tools are the most important factors that contribute to the success of BPR projects. These are vital factors that contribute to building an effective IT infrastructure for business processes (Al-Mashari & Zairi, 1999). BPR must be accompanied by strategic planning which addresses leveraging IT as a competitive tool (Weicher, et al., 1995).

An IT infrastructure is made up of physical assets, intellectual assets, shared services (Broadbent & Weill, 1997), and their linkages (Kayworth, et al., 1997). The way in which the IT infrastructure components are composed and their linkages determines the extent to which information resources can be delivered. An effective IT infrastructure composition process follows a top-down approach, beginning with business strategy and IS strategy and passing through designs of data, systems, and computer architecture (Malhotra, 1996). Linkages between the IT infrastructure components, as well as descriptions of their contexts of interaction, are important for ensuring integrity and consistency among the IT infrastructure components (Ross, 1998). Furthermore, IT standards have a major role in reconciling various infrastructure components to provide shared IT services that are of a certain degree of effectiveness to support business process applications, as well as to guide the process of acquiring, managing, and utilizing IT assets (Kayworth, et al., 1997). The IT infrastructure shared services and the human IT infrastructure components, in terms of their responsibilities and their needed expertise, are both vital to the process of the IT infrastructure composition. IT strategic alignment is approached through the process of integration between business and IT strategies, as well as between IT and organizational infrastructures (Al-Mashari & Zairi, 1999).

Most analysts view BPR and IT as irrevocably linked. Walmart, for example, would not have been able to reengineer the processes used to procure and distribute mass-market retail goods without IT. Ford was able to decrease its headcount in the procurement department by 75 percent by using IT in conjunction with BPR, in another well-known example (Weicher, et al., 1995). The IT infrastructure and BPR are interdependent in the sense that deciding the information requirements for the new business processes determines the IT infrastructure constituents, and a recognition of IT capabilities provides alternatives for BPR (Ross, 1998). Building a responsive IT infrastructure is highly dependent on an appropriate determination of business process

information needs. This, in turn, is determined by the types of activities embedded in a business process, and their sequencing and reliance on other organizational processes (Sabherwal & King, 1991).

Ongoing Continuous Improvement Many organizational change theorists hold a common view of organizations adjusting gradually and incrementally and responding locally to individual crises as they arise (Dooley & Johnson, 2001). BPR is a successive and ongoing process and should be regarded as an improvement strategy that enables an organization to make the move from traditional functional orientation to one that aligns with strategic business processes (Vakola & Rezgui, 2000). Continuous improvement is defined as the propensity of the organization to pursue incremental and innovative improvements in its processes, products, and services (Dooley & Johnson, 2001). The incremental change is governed by the knowledge gained from each previous change cycle. It is essential that the automation infrastructure of the BPR activity provides for performance measurements in order to support continuous improvements. It will need to efficiently capture appropriate data and allow access to appropriate individuals. To ensure that the process generates the desired benefits, it must be tested before it is deployed to the end users. If it does not perform satisfactorily, more time should be taken to modify the process until it does.

A fundamental concept for quality practitioners is the use of feedback loops at every step of the process and an environment that encourages constant evaluation of results and individual efforts to improve (Gore, 1999). At the end user’s level, there must be a proactive feedback mechanism that provides for and facilitates resolutions of problems and issues. This will also contribute to a continuous risk assessment and evaluation which are needed throughout the implementation process to deal with any risks at their initial state and to ensure the success of the reengineering efforts. Anticipating and planning for risk handling is important for dealing effectively with any risk when it first occurs and as early as possible in the BPR process (Clemons, 1995). It is interesting that many of the successful applications of reengineering described by its proponents are in organizations practicing continuous improvement programs. Hammer and Champy (1993) use the IBM Credit Corporation as well as Ford and Kodak, as examples of companies that carried out BPR successfully due to the fact that they had long-running continuous improvement programs (Gore, 1999).

In conclusion, successful BPR can potentially create substantial improvements in the way organizations do business and can actually produce fundamental improvements for business operations. However, in order to achieve that, there are some key success factors that must be taken into consideration when performing BPR. BPR success factors are a collection of lessons learned from reengineering projects and from these lessons common themes have emerged. In addition, the ultimate success of BPR depends on the people who do it and on how well they can be committed and motivated to be creative and to apply their detailed knowledge to the reengineering initiative. Organizations planning to undertake BPR must take into consideration the success factors of BPR in order to ensure that their reengineering related change efforts are comprehensive, well-implemented, and have minimum chance of failure.

4. Explain DFD & Data Dictionary? Explain in detail how the information requirement is determined for an organization?

Ans.

Data flow diagram

A data flow diagram (DFD) is a graphical representation of the "flow" of data through an information system, modeling its process aspects. Often they are a preliminary step used to create an overview of the system which can later be elaborated. DFDs can also be used for the visualization of data processing (structured design).

A DFD shows what kinds of data will be input to and output from the system, where the data will come from and go to, and where the data will be stored. It does not show information about the timing of processes, or information about whether processes will operate in sequence or in parallel (which is shown on a flowchart).

It is common practice to draw the context-level data flow diagram first, which shows the interaction between the system and external agents which act as data sources and data sinks. On the context diagram the system's interactions with the outside world are modelled purely in terms of data flows across the system boundary. The context diagram shows the entire system as a single process, and gives no clues as to its internal organization.

This context-level DFD is next "exploded", to produce a Level 0 DFD that shows some of the detail of the system being modeled. The Level 0 DFD shows how the system is divided into sub-systems (processes), each of which deals with one or more of the data flows to or from an external agent, and which together provide all of the functionality of the system as a whole. It also identifies internal data stores that must be present in order for the system to do its job, and shows the flow of data between the various parts of the system.

Data flow diagrams were proposed by Larry Constantine, the original developer of structured design based on Martin and Estrin's "data flow graph" model of computation.

Data flow diagrams (DFDs) are one of the three essential perspectives of the structured-systems analysis and design method SSADM. The sponsor of a project and the end users will need to be briefed and consulted throughout all stages of a system's evolution. With a data flow diagram, users are able to visualize how the system will operate, what the system will accomplish, and how the system will be implemented. The old system's dataflow diagrams can be drawn up and compared with the new system's data flow diagrams to draw comparisons to implement a more efficient system. Data flow diagrams can be used to provide the end user with a physical idea of where the data they input ultimately has an effect upon the structure of the whole system from order to dispatch to report. How any system is developed can be determined through a data flow diagram.

In the course of developing a set of levelled data flow diagrams the analyst/designers is forced to address how the system may be decomposed into component sub-systems, and to identify the transaction data in the data model.

There are different notations to draw data flow diagrams (Yourdon & Coad and Gane & Sarso), defining different visual representations for processes, data stores, data flow, and external entities.

Data dictionary

A data dictionary, or metadata repository, as defined in the IBM Dictionary of Computing, is a "centralized repository of information about data such as meaning, relationships to other data, origin, usage, and format."[1] The term may have one of several closely related meanings pertaining to databases and database management systems (DBMS):

a document describing a database or collection of databases an integral component of a DBMS that is required to determine its structure a piece of middleware that extends or supplants the native data dictionary of a DBMS

Documentation

The term Data Dictionary and Data Repository are used to indicate a more general software utility than a catalogue. A Catalogue is closely coupled with the DBMS Software; it provides the information stored in it to user and the DBA, but it is mainly accessed by the various software modules of the DBMS itself, such as DDL and DML compilers, the query optimiser, the transaction processor, report generators, and the constraint enforcer. On the other hand, a Data Dictionary is a data structure that stores meta-data, i.e., data about data. The Software package for a stand-alone Data Dictionary or Data Repository may interact with the software modules of the DBMS, but it is mainly used by the Designers, Users and Administrators of a computer system for information resource management. These systems are used to maintain information on system hardware and software configuration, documentation, application and users as well as other information relevant to system administration.

If a data dictionary system is used only by the designers, users, and administrators and not by the DBMS Software , it is called a Passive Data Dictionary; otherwise, it is called an Active Data Dictionary or Data Dictionary. An Active Data Dictionary is automatically updated as changes occur in the database. A Passive Data Dictionary must be manually updated.

The data Dictionary consists of record types (tables) created in the database by systems generated command files, tailored for each supported back-end DBMS. Command files contain SQL Statements for CREATE TABLE, CREATE UNIQUE INDEX, ALTER TABLE (for referential integrity), etc., using the specific statement required by that type of database.

Database users and application developers can benefit from an authoritative data dictionary document that catalogs the organization, contents, and conventions of one or more databases. This typically includes the names and descriptions of various tables and fields in each

database, plus additional details, like the type and length of each data element. There is no universal standard as to the level of detail in such a document, but it is primarily a weak kind of data.

The information requirement is determined for an organization

A data dictionary is a structured repository of data about data. It is a set of rigorous definitions of all DFD data elements and data structures. Most of the data flow in the DFD are specified here. Some of the most obvious ones are not shown here. The data dictionary entry for weekly timesheet specifies that this data flow is composed of three basic data entities - the employee name, employee ID and many occurrences of the two - tuple consisting of regular hours and overtime hours. The data dictionary for this DFD is shown below:

Weekly timesheet = Emplyee_Name + Employee_ID + {Regular_hours + overtime_hours}

Pay_rate = {Horly | Daily | Weekly} + Dollar_amount

Employee_Name = Last + First + Middle_Initial

Employee_ID = digit + digit + digit + digit

Once we have constructed a DFD and its associated data dictionary, we have to somehow verify that they are "correct". There can be no formal verification of a DFD, because what the DFD is modeling is not formally specify anywhere against which verification can be done. Human processes and rule of thumb must be used for verification. In addition to the walkthrough with the client, the analyst should look for common errors. Some common errors are

1.      Unlabeled data flows.

2.      Missing data flows: Information required by a process is not available.

3.      Extraneous data flows: Some information is not bein used in the process

4.      Consistency not maintained during refinement

5.      Missing processes

6.      Contains some control information

The DFDs should be carefully scrutinized to make sure that all the processes in the physical environment are shown in the DFD. It should also be ensured that none of the data flows is actually carrying control information.

5. What is ERP? Explain its existence before and its future after? What are the advantages & Disadvantages of ERP? What is Artificial Intelligence? How is it different from Neural Networks?

Ans.

Enterprise resource planning

Enterprise resource planning (ERP) systems integrate internal and external management information across an entire organization, embracing finance/accounting, manufacturing, sales and service, customer relationship management, etc. ERP systems automate this activity with an integrated software application. Their purpose is to facilitate the flow of information between all business functions inside the boundaries of the organization and manage the connections to outside stakeholders.

ERP systems can run on a variety of computer hardware and network configurations, typically employing a database as a repository for information.

Characteristics

ERP (Enterprise Resource Planning) systems typically include the following characteristics:

An integrated system that operates in real time (or next to real time), without relying on periodic updates.

A common database, which supports all applications.

A consistent look and feel throughout each module.

Installation of the system without elaborate application/data integration by the Information Technology (IT) department.

Connectivity to plant floor information

ERP systems connect to real–time data and transaction data in a variety of ways. These systems are typically configured by systems integrators, who bring unique knowledge on process, equipment, and vendor solutions.

Direct integration—ERP systems have connectivity (communications to plant floor equipment) as part of their product offering. This requires the vendors to offer specific support for the plant

floor equipment that their customers operate. ERP vendors must be expert in their own products, and connectivity to other vendor products, including competitors.

Database integration—ERP systems connect to plant floor data sources through staging tables in a database. Plant floor systems deposit the necessary information into the database. The ERP system reads the information in the table. The benefit of staging is that ERP vendors do not need to master the complexities of equipment integration. Connectivity becomes the responsibility of the systems integrator.

Enterprise appliance transaction modules (EATM)—These devices communicate directly with plant floor equipment and with the ERP system via methods supported by the ERP system. EATM can employ a staging table, Web Services, or system–specific program interfaces (APIs). The benefit of an EATM is that it offers an off–the–shelf solution.

Custom–integration solutions—Many system integrators offer custom solutions. These systems tend to have the highest level of initial integration cost, and can have a higher long term maintenance and reliability costs. Long term costs can be minimized through careful system testing and thorough documentation. Custom–integrated solutions typically run on workstation or server class computers.

Implementation

ERP's scope usually implies significant changes to staff work processes and practices. Generally, three types of services are available to help implement such changes—consulting, customization, and support. Implementation time depends on business size, number of modules, customization, the scope of process changes, and the readiness of the customer to take ownership for the project. Modular ERP systems can be implemented in stages. The typical project for a large enterprise consumes about 14 months and requires around 150 consultants. Small projects can require months; multinational and other large implementations can take years. Customization can substantially increase implementation times.

Process preparation

Implementing ERP typically requires changes in existing business processes.[14] Poor understanding of needed process changes prior to starting implementation is a main reason for project failure. It is therefore crucial that organizations thoroughly analyze business processes before implementation. This analysis can identify opportunities for process modernization. It also enables an assessment of the alignment of current processes with those provided by the ERP system. Research indicates that the risk of business process mismatch is decreased by:

Linking current processes to the organization's strategy;

Analyzing the effectiveness of each process;

Understanding existing automated solutions.

ERP implementation is considerably more difficult (and politically charged) in decentralized organizations, because they often have different processes, business rules, data semantics, authorization hierarchies and decision centers. This may require migrating some business units before others, delaying implementation to work through the necessary changes for each unit, possibly reducing integration (e.g. linking via Master data management) or customizing the system to meet specific needs.

A potential disadvantage is that adopting "standard" processes can lead to a loss of competitive advantage. While this has happened, losses in one area are often offset by gains in other areas, increasing overall competitive advantage.

Configuration

Configuring an ERP system is largely a matter of balancing the way the customer wants the system to work with the way it was designed to work. ERP systems typically build many changeable parameters that modify system operation. For example, an organization can select the type of inventory accounting—FIFO or LIFO—to employ, whether to recognize revenue by geographical unit, product line, or distribution channel and whether to pay for shipping costs when a customer returns a purchase.

Customization

ERP systems are theoretically based on industry best practices and are intended to be deployed "as is". ERP vendors do offer customers configuration options that allow organizations to incorporate their own business rules but there are often functionality gaps remaining even after the configuration is complete. ERP customers have several options to reconcile functionality gaps, each with their own pros/cons. Technical solutions include rewriting part of the delivered functionality, writing a homegrown bolt-on/add-on module within the ERP system, or interfacing to an external system. All three of these options are varying degrees of system customization, with the first being the most invasive and costly to maintain. Alternatively, there are non-technical options such as changing business practices and/or organizational policies to better match the delivered ERP functionality.

Key differences between customization and configuration include:

Customization is always optional, whereas the software must always be configured before use (e.g., setting up cost/profit center structures, organizational trees, purchase approval rules, etc.)

The software was designed to handle various configurations, and behaves predictably in any allowed configuration.

The effect of configuration changes on system behavior and performance is predictable and is the responsibility of the ERP vendor. The effect of customization is less predictable, is the customer's responsibility and increases testing activities.

Configuration changes survive upgrades to new software versions. Some customizations (e.g. code that uses pre–defined "hooks" that are called before/after displaying data screens) survive upgrades, though they require retesting. Other customizations (e.g. those involving changes to fundamental data structures) are overwritten during upgrades and must be reimplemented[26].

Customization Advantages:

Improves user acceptance

Offers the potential to obtain competitive advantage vis-à-vis companies using only standard features.

Customization Disadvantages:

Increases time and resources required to both implement and maintain.

Data becomes visible across the organization. Tasks that benefit from this integration include:

• Sales forecasting, which allows inventory optimization• Order tracking, from acceptance through fulfillment• Revenue tracking, from invoice through cash receipt• Matching purchase orders (what was ordered), inventory receipts (what arrived), and costing (what the vendor invoiced)Disadvantages of ERP• Customization is problematic.• Re–engineering business processes to fit the ERP system may damage competitiveness and/or divert focus from other critical activities• ERP can cost more than less integrated and/or less comprehensive solutions.• High switching costs increase vendor negotiating power vis a vis support, maintenance and upgrade expenses.• Overcoming resistance to sharing sensitive information between departments can divert management attention.• Integration of truly independent businesses can create unnecessary dependencies.• Extensive training requirements take resources from daily operations.

Artificial Intelligence

Artificial intelligence (AI) is the intelligence of machines and the branch of computer science that aims to create it. AI textbooks define the field as "the study and design of intelligent agents"

where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success.

John McCarthy, who coined the term in 1956, defines it as "the science and engineering of making intelligent machines.

Theoretical and computational neuroscience is the field concerned with the theoretical analysis and computational modeling of biological neural systems. Since neural systems are intimately related to cognitive processes and behaviour, the field is closely related to cognitive and behavioural modeling.The aim of the field is to create models of biological neural systems in order to understand how biological systems work. To gain this understanding, neuroscientists strive to make a link between observed biological processes (data), biologically plausible mechanisms for neural processing and learning (biological neural network models) and theory (statistical learning theory and information theory).

6. Distinguish between closed decision making system & open decision making system? What is – if ‘analysis? Why is more time spend in problem analysis & problem definition as compared to the time spends on decision analysis?

Ans.

CLASSIFICATION OF DECISION MAKING SYSTEMS [MIS]

 The decision making systems can be classified in a number of ways. There are two types of systems based on the manager’s knowledge about the environment.

A. Closed decision making system:

If the manager operates in a known environment then it is a closed decision making system. The conditions of the closed decision making system are:(a) The manager has a known set of decision alternatives and knows their outcomes fully in terms of value, if implemented.(b) The manager has a model, a method or a rule whereby the decision alternatives can be generated, tested, and ranked.(c) The manager can choose one of them, based on some goal or objective.

A few examples are:

a product mix problem,

an examination system to declare pass or fail, or

an acceptance of the fixed deposits.

B. Open decision making system:

If the manager operates in an environment not known to him, then the decision making system is termed as an open decision making system. The conditions of this system are:

(a) The manager does not know all the decision alternatives.

(b) The outcome of the decision is also not known fully. The knowledge of the outcome may be a probabilistic one.

(c) No method, rule or model is available to study and finalize one decision among the set of decision alternatives.

(d) It is difficult to decide an objective or a goal and, therefore, the manager resorts to that decision, where his aspirations or desires are met best.

Deciding on the possible product diversification lines, the pricing of a new product, and the plant location, are some decision making situations which fall in the category of the open decision making systems.

The MIS tries to convert every open system to a closed decision making system by providing information support for the best decision. The MIS gives the information support, whereby the manager knows more and more about the environment and the outcomes, he is able to generate the decision alternatives, test them and select one of them. A good MIS achieves this.

Open and Closed Systems

A system is commonly defined as a group of interacting units or elements that have a common purpose. The units or elements of a system can be cogs, wires, people, computers, and so on. Systems are generally classified as open systems and closed systems and they can take the form of mechanical, biological, or social systems. Open systems refer to systems that interact with other systems or the outside environment, whereas closed systems refer to systems having relatively little interaction with other systems or the outside environment. For example, living organisms are considered open systems because they take in substances from their environment such as food and air and return other substances to their environment. Humans, for example, inhale oxygen out of the environment and exhale carbon dioxide into the environment. Similarly, some organizations consume raw materials in the production of products and emit finished goods and pollution as a result. In contrast, a watch is an example of a closed system in that it is a relatively self-contained, self-maintaining unit that has little interacts or exchange with its environment.

All systems have boundaries, a fact that is immediately apparent in mechanical systems such as the watch, but much less apparent in social systems such as organizations. The boundaries of open systems, because they interact with other systems or environments, are more flexible than those of closed systems, which are rigid and largely impenetrable. A closed-system perspective views organizations as relatively independent of environmental influences. The closed-system approach conceives of the organization as a system of management, technology, personnel, equipment, and materials, but tends to exclude competitors, suppliers, distributors, and governmental regulators. This approach allows managers and organizational theorists to analyze problems by examining the internal structure of a business with little consideration of the external environment. The closed-system perspective basically views an organization much as a thermostat; limited environmental input outside of changes in temperature is required for effective operation. Once set, thermostats require little maintenance in their ongoing, self-reinforcing function. While the closed-system perspective was dominant through the 1960s,

organization scholarship and research subsequently emphasized the role of the environment. Up through the 1960s, it was not that managers ignored the outside environment such as other organizations, markets, government regulations and the like, but that their strategies and other decision-making processes gave relatively little consideration to the impact these external forces might have on the internal operations of the organization.

Open-systems theory originated in the natural sciences and subsequently spread to fields as diverse as computer science, ecology, engineering, management, and psychotherapy. In contrast to closed-systems, the open-system perspective views an organization as an entity that takes inputs from the environment, transforms them, and releases them as outputs in tandem with reciprocal effects on the organization itself along with the environment in which the organization operates. That is, the organization becomes part and parcel of the environment in which it is situated. Returning for a moment to the example of biological systems as open-systems, billions of individual cells in the human body, themselves composed of thousands of individual parts and processes, are essential for the viability of the larger body in which they are a part. In turn, "macro-level" processes such as eating and breathing make the survival of individual cells contingent on these larger processes. In much the same way, open-systems of organizations accept that organizations are contingent on their environments and these environments are also contingent on organizations.

As an open-systems approach spread among organizational theorists, managers began incorporating these views into practice. Two early pioneers in this effort, Daniel Katz and Robert Kahn, began viewing organizations as open social systems with specialized and interdependent subsystems and processes of communication, feedback, and management linking the subsystems. Katz and Kahn argued that the closed-system approach fails to take into account how organizations are reciprocally dependent on external environments. For example, environmental forces such as customers and competitors exert considerable influence on corporations, highlighting the essential relationship between an organization and its environment as well as the importance of maintaining external inputs to achieve a stable organization.

Furthermore, the open-system approach serves as a model of business activity; that is, business as a process of transforming inputs to outputs while realizing that inputs are taken from the external environment and outputs are placed into this same environment. Companies use inputs such as labor, funds, equipment, and materials to produce goods or to provide services and they design their subsystems to attain these goals. These subsystems are thus analogous to cells in the body, the organization itself is analogous to the body, and external market and regulatory conditions are analogous to environmental factors such as the quality of housing, drinking water, air and availability of nourishment.

The production subsystem, for example, focuses on converting inputs into marketable outputs and often constitutes a primary purpose of a company. The boundary subsystem's goal is to obtain inputs or resources, such as employees, materials, equipment, and so forth, from the

environment outside of the company, which are necessary for the production subsystem. This subsystem also is responsible for providing an organization with information about the environment. This adaptive subsystem collects and processes information about a company's operations with the goal of aiding the company's adaptation to external conditions in its environment. Another subsystem, management, supervises and coordinates the other subsystems to ensure that each subsystem functions efficiently. The management subsystem must resolve conflicts, solve problems, allocate resources, and so on.

To simplify the process of evaluating environmental influences, some organizational theorists use the term "task environment" to refer to aspects of the environment that are immediately relevant to management decisions related to goal setting and goal realization. The task environment includes customers, suppliers, competitors, employees, and regulatory bodies. Furthermore, in contrast to closed-systems, the open-system perspective does not assume that the environment is static. Instead, change is the rule rather than the exception. Consequently, investigation of environmental stability and propensity to change is a key task of a company, making the activities of an organization contingent on various environmental forces. As an open system, an organization maintains its stability through feedback, which refers to information about outputs that a system obtains as an input from its task environment. The feedback can be positive or negative and can lead to changes in the way an organization transforms inputs to outputs. Here, the organization acts as a thermostat, identified previously as an example of a relatively closed-system. The difference between closed-systems and open-systems, then, is in the complexity of environmental interactions. Closed-systems assume relatively little complexity; a thermostat is a simple device dependent mainly on temperature fluctuations. Conversely, open-system such as the human body and modern organizations are more intricately dependent on their environments. The point is that closed-systems versus open-systems do not represent a dichotomy, but rather a continuum along which organizations are more open or less open to their environments. The key defining variable governing this degree of openness is the complexity of the environment in which the organization is situated.

Managers must take into consideration their organization's position along the open-closed continuum. The Linux computer operating system, for instance, is "open-source" and Red Hat, Inc., the corporation selling the bundled revisions-the multiple inputs from geographically dispersed users-represents an organization that would cease to exist if it were not for an open-systems perspective. Thus, stable environments with low complexity are more consistent with a relatively closed-system or mechanistic management style, while rapidly-changing environments are more consistent with flexible, decentralized, or "organic" management styles.

SET 2

1. How hardware & software support in various MIS activities of the organization? Explain the transaction stages from manual system to automated systems?

Ans.

Hardware   support for   MIS

Generally hardware in the form of personal computers and peripherals like printers, fax machines, copier, scanners etc are used in organization to support various MIS activities of the organization.

Advantages of a PC: 

Advantages a personal computer offers are –

a) Speed – A  PC can process data at a very high speed. It can process millions of instructions within fraction of seconds. 

b) Storage – A PC can store large quantity of data in a small space. It eliminates the need of storing the conventional office flat files and box files which requires lots of space. The storage system in a PC is such that the information can be transferred from place to another place in electronic form. 

c) Communication – A PC on the network can offer great support as  a communicator in communicating information in the forms of text and images. Today a PC with internet is used as a powerful tool of communication for every business activity. 

d) Accuracy – A PC is highly reliable in the sense that it could be used to perform calculations continuously for hours with a great degree of accuracy. It is possible to obtain mathematical results correct up to a great degree of accuracy. 

e) Conferencing – A PC with internet offers facility of video conferencing worldwide.  Business people  across  the globe travel  a lot to meet  their business  partner,  colleagues,  customers  etc  to discuss about business activities. 

By video conferencing inconvenience of traveling can be avoided.

Input unit is used to give input to the processor. Examples of input unit –Keyboard, scanner, mouse, bar code reader etc.

A processor refers to unit which processes the input received the way it has been instructed. In a computer the processor is the CPU – Central Processing Unit. It does all mathematical calculations, logical tasks, storing details in the memory etc. 

Output unit is used to give output s from the computer. Examples of output unit –Monitor, printer, speakers etc.

Classification of computers: 

Computers are classified as follows –

a) Depending upon the processor used – eg: Intel PI, PII, PIII, PIV, AMD, Celerons etc.

b) Depending upon the purpose for which it is used a Computer may be a general purpose computer or a specific purpose computer. General purpose computers are the ones used for general tasks like business analysis, letter typing, generating reports for management decisions, scheduling activities, preparing balance sheets, invoice etc,  Specific purpose computers are custom build for specific  tasks  like space research, weather forecasting,  satellite sensing etc.

Unit computers are designed to perform tasks for which they are intended for and for no other applications. 

c) Depending upon the size: A computer may be classified based upon its size and voluminous computing speed as micro computers, mini computers, main frames and super computers. Super computer is the largest in size and also fastest in computing speed.

MIS (Managing Information Software) Software

MIS software helps for managing your accounts, inventory, taxation, payroll, stock, banking, financial and other records.

MIS involves all aspects of gathering, storing, tracking, retrieving and using information within a business or organization. All the policies, procedures, and practices that direct an organization's operations and the staff that interact with the information, combined with the software and hardware, comprise an information system.

MIS Software was developed specifically for the management and tracking of every transaction in regulated environments. Our high-performance, relational database program tracks and maintains accurate, real-time information, yet it is easy to implement and use.

This MIS Software manages your Daily Schedules, Job Summary, Inventory, Accounts and all the Daily transaction. Records include Full Accounting and Inventory Features.

We offer complete custom development Information systems that can take care of business operations.

Management Information (MIS), as it is popularly known, deals with the entry and exit of information in a computer system specially designed for the business purpose. It has several subcomponents like the Decision support system, marketing information system, financial information system, HR information system, production information system and many more.

MIS Manager is a readily implementable solution, with capability to interface with any existing Data source towards faster and efficient implementation and management. With capability to deploy across the Enterprise, MIS Manager can provide the advantage of managing outputs and Reports generated from various sources and technologies.

Our System Offers Complete Solutions, which include:

Cost Management Product Development Inventory Management Integration with Accounting & Invoice Systems Document Management System MIS Features: Speed of Deployment Customer Support Ease to Use Functionality Achievement of business goals

Many inventory reports are available. There are alphabetizing methods that can be used. You can print physical inventory sheets, parts under minimum stocking quantity, value of inventory (by sales category) and replacement cost.

2. Explain the various behavioral factors of management organization? As per Porter, how can performance of individual corporations be determined?

Ans.

Organizational behavior

Organizational behavior is the study of individuals and their actions within the context of the organization in a workplace setting. It is an interdisciplinary field that includes sociology, psychology, communication, and management; and it complements the academic studies of organizational theory (which is more macro-level) and human resource studies (which is more applied and business-related). It may also be referred to as organizational studies or organizational science. The field has its roots in industrial and organizational psychology.

Overview

Organizational studies encompass the study of organizations from multiple viewpoints, methods, and levels of analysis. For instance, one textbook divides these multiple viewpoints into three perspectives: modern, symbolic, and postmodern. Another traditional distinction, present especially in American academia, is between the study of "micro" organizational behaviour — which refers to individual and group dynamics in an organizational setting — and "macro" strategic management and organizational theory which studies whole organizations and industries, how they adapt, and the strategies, structures and contingencies that guide them. To this distinction, some scholars have added an interest in "meso" scale structures - power, culture, and the networks of individuals and i.e. ronit units in organizations — and "field" level analysis which study how whole populations of organizations interact.

Whenever people interact in organizations, many factors come into play. Modern organizational studies attempt to understand and model these factors. Like all modernist social sciences, organizational studies seek to control, predict, and explain. There is some controversy over the ethics of controlling workers' behavior, as well as the manner in which workers are treated (see Taylor's scientific management approach compared to the human relations movement of the 1940s). As such, organizational behaviour or OB (and its cousin, Industrial psychology) have at times been accused of being the scientific tool of the powerful.Those accusations notwithstanding, OB can play a major role in organizational development, enhancing organizational performance, as well as individual and group performance/satisfaction/commitment.

One of the main goals of organizational theorists is, according to Simms (1994) "to revitalize organizational theory and develop a better conceptualization of organizational life." An organizational theorist should carefully consider levels assumptions being made in theory, and is concerned to help managers and administrators.

While Classical philosophies rarely took upon a task of developing a specific theory of organizations, some had used implicit conceptions of general organization in construct views on politics and virtue; the Greek philosopher Plato, for example, wrote about the essence of leadership, emphasized the importance of specialization and discussed a primordial form of incentive structures in speculating how to get people to embody the goal of the just city in The Republic. Aristotle also addressed such topics as persuasive communication. The writings of 16th century Italian philosopher Niccolò Machiavelli laid the foundation for contemporary work on organizational power and politics. In 1776, Adam Smith advocated a new form of organizational structure based on the division of labour. One hundred years later, German sociologist Max Weber wrote about rational organizations and initiated discussion of charismatic leadership. Soon after, Frederick Winslow Taylor introduced the systematic use of goal setting and rewards to motivate employees. In the 1920s, Australian-born Harvard professor Elton Mayo and his colleagues conducted productivity studies at Western Electric's Hawthorne plant in the United States.

Though it traces its roots back to Max Weber and earlier, organizational studies began as an academic discipline with the advent of scientific management in the 1890s, with Taylorism representing the peak of this movement. Proponents of scientific management held that rationalizing the organization with precise sets of instructions and time-motion studies would lead to increased productivity. Studies of different compensation systems were carried out.

After the First World War, the focus of organizational studies shifted to how human factors and psychology affected organizations, a transformation propelled by the identification of the Hawthorne Effect. This Human Relations Movement focused on teams, motivation, and the actualization of the goals of individuals within organizations.

Prominent early scholars included Chester Barnard, Henri Fayol, Frederick Herzberg, Abraham Maslow, David McClelland, and Victor Vroom.

The Second World War further shifted the field, as the invention of large-scale logistics and operations research led to a renewed interest in rationalist approaches to the study of organizations. Interest grew in theory and methods native to the sciences, including systems theory, the study of organizations with a complexity theory perspective and complexity strategy. Influential work was done by Herbert Alexander Simon and James G. March and the so-called "Carnegie School" of organizational behavior.

In the 1960s and 1970s, the field was strongly influenced by social psychology and the emphasis in academic study was on quantitative research. An explosion of theorizing, much of it at Stanford University and Carnegie Mellon, produced Bounded Rationality, Informal Organization, Contingency Theory, Resource Dependence, Institutional Theory, and Organizational Ecology theories, among many others.

Starting in the 1980s, cultural explanations of organizations and change became an important part of study. Qualitative methods of study became more acceptable, informed by anthropology,psychology and sociology. A leading scholar was Karl Weick.

Methods used in organizational studies

A variety of methods are used in organizational studies. They include quantitative methods found in other social sciences such as multiple regression, non-parametric statistics, time series analysis,Meta-analysis and ANOVA. In addition, computer simulation in organizational studies has a long history in organizational studies. Qualitative methods are also used, such as ethnography, which involves direct participant observation, single and multiple case analysis, grounded theory approaches, and other historical methods. Fred Arthur.

Systems framework

The systems framework is also fundamental to organizational theory as organizations are complex dynamic goal-oriented processes. One of the early thinkers in the field was Alexander Bogdanov, who developed his Tectology, a theory widely considered a precursor of Bertalanffy's General Systems Theory, aiming to model and design human organizations. Kurt Lewin was particularly influential in developing the systems perspective within organizational theory and coined the term "systems of ideology", from his frustration with behavioural psychologies that became an obstacle to sustainable work in psychology (see Ash 1992: 198-207). The complexity theory perspective on organizations is another systems view of organizations.

The systems approach to organizations relies heavily upon achieving negative entropy through openness and feedback. A systemic view on organizations is transdisciplinary and integrative. In other words, it transcends the perspectives of individual disciplines, integrating them on the basis of a common "code", or more exactly, on the basis of the formal apparatus provided by systems theory. The systems approach gives primacy to the interrelationships, not to the elements of the system. It is from these dynamic interrelationships that new properties of the system emerge. In recent years,systems thinking has been developed to provide techniques for studying systems in holistic ways to supplement traditional reductionistic methods. In this more recent tradition, systems theory in organizational studies is considered by some as a humanistic extension of the natural sciences.

Managerial roles

In the late 1960s Henry Mintzberg, a graduate student at MIT undertook a careful study of five executives to determine what those managers did on their jobs. On the basis of his observations, Mintzberg classifies managerial roles into 3 categories

1. Interpersonal Roles

2. Decisional Roles

3. Informational Roles

Rational Decision-Making Model Scientific management Garbage can model

Theories of decision making can be subdivided into three categories

Normative (concentrates on how decision should be made) Descriptive (concerned with how the thinker came up with their judgement) Prescripted (aim to improve decision making)

Motivation in organizations

Motivation the forces either internal or external to a person that arouse enthusiasm and resistance to pursue a certain course of action. According to Baron et al. (2008):[  "Although motivation is a broad and complex concept, organizational scientists have agreed on its basic characteristics. Drawing from various social sciences, we define motivation as the set of processes that arouse, direct, and maintain human behavior toward attaining some goal"

3. Compare various types of development aspect of Information System? Explain the various stages of SDLC?

Ans.

The Various Types of Information Systems Analysis Projects

There are three types of information systems projects: manual, manual to automated, and reautomation. The last, reautomation, has four subtypes: system rewrite, system redesign and redevelopment, system enhancement, and system maintenance. Each of these involves different, and yet similar, work. The work is similar in that the development activities which are involved in each follow the same general phases and approach. They are different in that the environment that the analyst must examine has substantially different characteristics.

This chapter examines each of the various types of analysis projects, along with a brief discussion of the Gibson-Nolan electronic data processing (EDP) stages of growth theory and its impact on the analysis process. In addition there is a brief discussion of the Anthony model of organizational structure.

A definition

Personal Computer (PC) - also known as microcomputers or workstations, by the model name of the specific vendor (i.e.  Apple , Macintosh , or PS/2 or by the brand name, model and speed of the processor (i.e. Pentium, Intel or 486/33 Any combination of processor, input device and output device designed for use by a single individual.  Personal computers may also be called workstations.

Personal computers may have a character orientation, a graphical orientation, may be connected to other personal computers, or may operate in a stand alone mode, and may or may not have connectivity to a mainframe. 

Personal computer software is normally characterized by an operating system which provides basic file access, management  and display services and well as application scheduling and management.

Reasons For Initiating Information Systems Analysis Projects

Information systems analysis projects are initiated for a variety of reasons.  These include:

As part of a program of System Modernization.

Many firms undertake a series of projects to upgrade all data processing technology - both hardware, operating system and support software and automated business applications.  This is

usually initiated as part of a desire to eliminate the older centralized applications and to replace them with newer personal computer based system.

A change in the basic aspects of the user's functional role

As the companies redesign their basic processes either as a result of a continuous improvement effort, or a more radical Business Process Reengineering effort

A change in company strategic objectives

Increased competition, both in the local and international markets have forced many firms to rethink not only how they do business but also what business they should be in.  In some instances, manufacturing firms are becoming service firms, primary producers are becoming assemblers of components produced by others, companies are changing their lines of business, and reexamining the customer base they are focused on.  Large firms are divesting themselves of divisions and whole product lines and reverting back to what they feel are their core businesses.

A need for increased performance, greater or different functionality, different operating characteristics, or increased user friendliness from the automated systems

As business conditions change, there are increased user demands for greater or in some cases  different functionality from the exiting systems.  Increased user computer literacy, and exposure to PC applications with Graphical User Interfaces (GUI) have changed user expectations for and tolerance of sometimes awkward, character based systems.

A need for more direct and immediate access to the firm's automated files.

The exposure to the wide variety of workstation based tools and systems.  Most user workstations or PCs have extensive files of their own.  The data in these files may have come from information keyed in by the user, transferred to the user’s machine from another user machine via diskette, or down-loaded to the user’s machine from either another workstation or from a mini-computer or mainframe via a file transfer mechanism.  These transfers are time consuming and awkward.  Users are increasingly looking for faster access to data regardless of where it resides.

A need to upgrade the system to take advantage of more current technology.

Vendors are increasing the power (speed and capacity) of their offerings.  Capacity includes both Random Access Memory (RAM) and hard drive storage. The speed, capacity and variety of peripheral equipment (printers, plotters, scanners, fax, CD-ROM (Compact Disk - Read Only Memory), high resolution  monitors, etc.) continues to expand as well.  As capacity and speed increase and as more and more peripheral capability becomes available the variety of applications available increases as well and users rush to acquire these new tools.

A need to clean up the system -

All computer systems tend to get cluttered over time with a patchwork of add-on modules, files, and processes.  These pieces do not work together in a harmonious manner but rather interact awkwardly and inefficiently.

Given the above, we can no long assume that a systems analysis project has been undertaken as the first step toward developing a new or improved .application.  Nor can we assume that  many of the constraints that applied to the development of mainframe systems are still in effect.  In fact we can no longer assume that we will be developing a mainframe resident system at all.  Today’s systems can reside on a variety of hardware platforms and take a variety of forms.

The Three Types of Information Systems Analysis Projects

The scope and magnitude of the functional and procedural changes may be fairly narrow or wide ranging. In some cases, aside from re-coding the system, there may be no changes in functionality at all.

Given the variety of reasons for a project being undertaken, the starting point may also be quite different from project to project. These starting points reflect the differences in current user processing environments and the current level of user automation. Because of these differences in current user processing environments and user automation, information systems projects can be categorized into three types.

1. Manual2. Manual to automated3. Re automation4. The last, re automation, has four subtypes.

a) System rewriteb) System redesign and redevelopmentc) System enhancementd) System maintenance

From an analysis perspective, each of these types of projects involves different, and yet similar, work. The work is similar in that the development activities, which are involved in each, follow the same general phases and approach. They are different in that each of the starting or current environments that the analyst must examine have substantially different characteristics. Briefly, these six environmental types and subtypes are as follows.

Manual

From the analyst's viewpoint, this is the simplest environment in that all the components of the environment are overt. That is, they are clearly visible from observation and analysis. All work is performed by user personnel, who work directly with their files, forms, and documents. The processing of these forms and documents, the work flows, and the individual steps are easily followed.

At their core all systems analysis projects are concerned with the examination of what are, or once were, essentially manual operations. In fact, it is helpful, regardless of the type of project, to view all the activities of the user as if they were still being performed by hand. This allows the analyst to examine in detail each task being performed, each data operation, each data movement, and each data carrier (a data carrier is a piece of paper, a form, a report, a worksheet, a transaction, etc.).

The analyst's task in the manual environment is to simplify the work flows, streamline the processes, reduce redundant processing, rearrange the tasks so as to ensure more orderly processing, and ensure that the forms, documents, and reports contain all necessary data. Each task, and each task step, must be examined to determine (a) if its execution is appropriate and (b) if it is appropriately defined, positioned, and performed.

The results of the analysis of manual systems are usually new or revised standards and procedures which clearly define the processing sequence for the task to be performed and the rules which govern their performance. In addition the analyst may develop new input forms, control procedures, monitoring procedures, and reports. The output from the analysis may also include new or revised work and data flow diagrams.

Manual to automated

Working in this type of environment differs from working in the strictly manual environment in that the analyst's task is to determine whether the manual environment, in whole or in part, can be augmented by automation, and if so, to what extent. The existing environment must be analyzed in the same manner as the purely manual, but as the analysis progresses, the analyst must also find ways of substituting automated processing for manual processing. To accomplish this, the analyst must break each process and task into its component steps and determine if the rules for performing the step lend themselves to machine automation.

The analyst's output for this type of project closely resembles that produced from the strictly manual project. However, here the analyst must also develop (a) new, input forms suitable to an automated environment, (b) file content requirements for ongoing master and transaction files, (c) report layouts, and (d) a processing flow which intermixes the original and unmodified manual processes, new manual processes, and new automated processes. The analyst must also make a determination as to the costs involved in the automation process, provide project schedules, and make hardware and software analyses and recommendations.

Reautomation

There have been many attempts to set down analytical and design methodologies for development projects in automated environments. What many of them ignore is that there are different types of automated business environments, which, while seemingly similar, must in fact be treated differently.

What distinguishes these environments is the extent and depth of automation. Early analysis methodologies were predicated on a manual environment. The aim of the analysis was to develop an automated solution to user business problems. In today's environment, most firms of any size have existing levels of automation. Many in fact have gone through two and three rounds of automation and reautomation.

Many of the existing processes and procedures are either totally automated or were developed as a result of a partial automation of the user area. Many of the forms and transaction flows within this type of environment are automated or semi-automated.

This prior automation poses a trap for the unwary analyst in that the currently used forms and documents of the business may in fact have been designed to support and accommodate an automated system. These automated systems may have been designed for the business using a level of technology which is now outdated or inefficient, or for a set of user requirements or a business environment which has since become wholly or partially obsolete. Additionally, these forms and documents are the result of some prior analyst's efforts and may not in fact reflect the natural information or data needs of the firm.

The processing flows themselves may be unnatural, to the extent that they reflect the intrusion of automated processing sequences. These flows may have been structured to accommodate the needs of the then prevalent technology rather than the needs of the business. Each of the documents, transactions and process flows must be reexamined in the light of the current business environment and the current business processing needs. They may merely need to be refurbished, or they may need to be scrapped entirely in favor of a new and more streamlined processing flow.

The analyst must look with care on batch flows, "processing windows," and transaction holding queues. These constraints may have been imposed on the processing environment by the requirements of prior automation efforts, most probably implemented under what is now an outdated, or, worse, obsolete technology. Re automation is a major type of project which incorporates the following sub-categories.

Platform is the term used to distinguish between the different classes or sizes of computing machinery –mainframe, minicomputer and microcomputer (or personal computer or workstation), between the various operating systems on each machine, and in some cases between stand-alone machines and networked machines.

In some cases the term platform is used to distinguish between one combination of machine and software and  some other combination.

Throughout this book we will use the qualified term hardware platform to represent  differences in computing machinery and the qualified term software platform to represent differences in operating systems on a given class of machinery.

The Corporate level

This level consists those information and business systems which are designed for use by all areas of the corporation.   These systems are normally characterized by:

1. Specific functional area responsibility2. Centralized development and maintenance3. Requirements that conform to and are constrained by corporate-wide policies and

procedures4. Cross-function or cross-business boundary use5. Mainframe or Minicomputer residence6. Supported by additional, non-automated forms7. Augmented by extensive manual procedures.

The Departmental Level

This level consists of information and business systems which are designed for use by a specific area or areas of the corporation.  These systems are normally characterized by:

1. Specific functional area responsibility2. Central development and maintenance, local development and maintenance or vendor

supplied and supported3. Support for a single function or activity4. Minicomputer or Mainframe residence

The Personal Level

This level consists of information and business systems which are designed for use by a single individual.  These systems are normally characterized by:

1. Personal computer residence2. Support for a single user3. Customized processing or general facility4. Customized settings.5. User built or vendor supplied and maintained.

4. Compare & Contrast E-enterprise business model with traditional business organization model? Explain how in E-enterprise manager role & responsibilities are changed? Explain how manager is a knowledge worker in E-enterprise?

Ans.

Business process modeling

Business Process Modeling (BPM) in systems engineering is the activity of representing

processes of an enterprise, so that the current process may be analyzed and improved. BPM is

typically performed by business analysts and managers who are seeking to improve process

efficiency and quality. The process improvements identified by BPM may or may not require

Information Technology involvement, although that is a common driver for the need to model a

business process, by creating a process master.

Change management programs are typically involved to put the improved business processes

into practice. With advances in technology from large platform vendors, the vision of BPM

models becoming fully executable (and capable of simulations and round-trip engineering) is

coming closer to reality every day.

Techniques to model business process such as the flow chart, functional flow block

diagram, control flow diagram, Gantt chart, PERT diagram, and IDEF have emerged since the

beginning of the 20th century. The Gantt charts were among the first to arrive around 1899, the

flow charts in the 1920s, Functional Flow Block Diagram and PERT in the 1950s, Data Flow

Diagrams and IDEF in the 1970s. Among the modern methods are Unified Modeling

Language and Business Process Modeling Notation. Still, these represent just a fraction of the

methodologies used over the years to document business processes.[1] The term "business process

modeling" itself was coined in the 1960s in the field of systems engineering by S. Williams in

his 1967 article "Business Process Modeling Improves Administrative Control".[2] His idea was

that techniques for obtaining a better understanding of physical control systems could be used in

a similar way for business processes. It took until the 1990s before the term became popular.

In the 1990s the term "process" became a new productivity paradigm.[3] Companies were

encouraged to think in processes instead of functions and procedures. Process thinking looks at

the chain of events in the company from purchase to supply, from order retrieval to sales etc. The

traditional modeling tools were developed to picture time and costs, while modern methods focus

on cross-function activities. These cross-functional activities have increased severely in number

and importance due to the growth of complexity and dependencies. New methodologies such

as business process redesign, business process innovation, business process

management, integrated business planning among others all "aiming at improving processes

across the traditional functions that comprise a company".

In the field of software engineering the term "business process modeling" opposed the

common software process modeling, aiming to focus more on the state of the practice

during software development. In that time early 1990s all existing and new modeling techniques

to picture business processes were considered and called "business process modeling languages."

In the Object Oriented approach, it was considered to be an essential step in the specification of

Business Application Systems. Business process modeling became the base of new

methodologies, that for example also supported data collection, data flow analysis, process flow

diagrams and reporting facilities. Around 1995 the first visually oriented tools for business

process modeling and implementation were being presented.

Business process

A business process is a collection of related, structured activities or tasks that produce a specific

service or product (serve a particular goal) for a particular customer or customers. There are

three main types of business processes:

1. Management processes, the processes that govern the operation of a system. Typical

management processes include "Corporate Governance" and "Strategic Management".

2. Operational processes, processes that constitute the core business and create the primary

value stream. Typical operational processes are Purchasing, Manufacturing, Marketing,

and Sales.

3. Supporting processes, which support the core processes. Examples

include Accounting, Recruitment, Technical support.

A business process can be decomposed into several sub-processes, which have their own

attributes, but also contribute to achieving the goal of the super-process. The analysis of business

processes typically includes the mapping of processes and sub-processes down to activity level.

A business process model is a model of one or more business processes, and defines the ways in

which operations are carried out to accomplish the intended objectives of an organization. Such a

model remains an abstraction and depends on the intended use of the model. It can describe the

workflow or the integration between business processes. It can be constructed in multiple levels.

A business reference model is a reference model, concentrating on the functional and

organizational aspects of an enterprise, service organization or government agency. In general

a reference model is a model of something that embodies the basic goal or idea of something and

can then be looked at as a reference for various purposes. A business reference model is a means

to describe the business operations of an organization, independent of the organizational

structure that perform them. Other types of business reference model can also depict the

relationship between the business processes, business functions, and the business area’s business

reference model. These reference models can be constructed in layers, and offer a foundation for

the analysis of service components, technology, data, and performance.

The most familiar business reference model is the Business Reference Model of the US Federal

Government. That model is a function-driven framework for describing the business operations

of the Federal Government independent of the agencies that perform them. The Business

Reference Model provides an organized, hierarchical construct for describing the day-to-day

business operations of the Federal government. While many models exist for describing

organizations - organizational charts, location maps, etc. - this model presents the business using

a functionally driven approach.

A business model, which may be considered an elaboration of a business process model,

typically shows business data and business organizations as well as business processes. By

showing business processes and their information flows a business model allows business

stakeholders to define, understand, and validate their business enterprise. The data model part of

the business model shows how business information is stored, which is useful for

developing software code. See the figure on the right for an example of the interaction between

business process models and data models.

Usually a business model is created after conducting an interview, which is part of the business

analysis process. The interview consists of a facilitator asking a series of questions to extract

information about the subject business process. The interviewer is referred to as a facilitator to

emphasize that it is the participants, not the facilitator, who provide the business process

information. Although the facilitator should have some knowledge of the subject business

process, but this is not as important as the mastery of a pragmatic and rigorous method

interviewing business experts. The method is important because for most enterprises a team of

facilitators is needed to collect information across the enterprise, and the findings of all the

interviewers must be compiled and integrated once completed.

Business models are developed as defining either the current state of the process, in which case

the final product is called the "as is" snapshot model, or a concept of what the process should

become, resulting in a "to be" model. By comparing and contrasting "as is" and "to be" models

the business analysts can determine if the existing business processes and information systems

are sound and only need minor modifications, or if reengineering is required to correct problems

or improve efficiency. Consequently, business process modeling and subsequent analysis can be

used to fundamentally reshape the way an enterprise conducts its operations.

Business process reengineering (BPR) is an approach aiming at improvements by means of

elevating efficiency and effectiveness of the processes that exist within and across organizations.

The key to business process reengineering is for organizations to look at their business processes

from a "clean slate" perspective and determine how they can best construct these processes to

improve how they conduct business.

Business process reengineering (BPR) began as a private sector technique to help organizations

fundamentally rethink how they do their work in order to dramatically improve customer service,

cut operational costs, and become world-class competitors. A key stimulus for reengineering has

been the continuing development and deployment of sophisticated information systems and

networks. Leading organizations are becoming bolder in using this technology to support

innovative business processes, rather than refining current ways of doing work

Business process management

Business process management is a field of management focused on aligning organizations with

the wants and needs of clients. It is a holistic management approach that promotes business

effectiveness and efficiency while striving for innovation, flexibility and integration with

technology. As organizations strive for attainment of their objectives, business process

management attempts to continuously improve processes - the process to define measure and

improve your processes – a "process optimization" process.

5. What do you understand by service level Agreements (SLAs)? Why are they needed? What is the role of CIO in drafting these? Explain the various security hazards faced by an IS?

Ans.

Service-level agreement

A service-level agreement (SLA) is a part of a service contract where the level of service is

formally defined. In practice, the term SLA is sometimes used to refer to the contracted delivery

time (of the service) or performance. As an example, internet service providers will commonly

include service level agreements within the terms of their contracts with customers to define the

level(s) of service being sold in plain language terms. In this case the SLA will typically have a

technical definition in terms of mean time between failures (MTBF), mean time to

repair or mean time to recovery (MTTR); various data rates; throughput; jitter; or similar

measurable details.

A service-level agreement is a negotiated agreement between two parties, where one is the

customer and the other is the service provider. This can be a legally binding formal or an

informal "contract" (for example, internal department relationships). Contracts between the

service provider and other third parties are often (incorrectly) called SLAs – because the level of

service has been set by the (principal) customer, there can be no "agreement" between third

parties; these agreements are simply a "contract." Operational-level agreements or OLAs,

however, may be used by internal groups to support SLAs.

The SLA records a common understanding about services, priorities, responsibilities, guarantees,

and warranties. Each area of service scope should have the "level of service" defined. The SLA

may specify the levels of availability, serviceability, performance, operation, or other attributes

of the service, such as billing. The "level of service" can also be specified as "target" and

"minimum," which allows customers to be informed what to expect (the minimum), while

providing a measurable (average) target value that shows the level of organization performance.

In some contracts, penalties may be agreed upon in the case of non-compliance of the SLA (but

see "internal" customers below). It is important to note that the "agreement" relates to the

services the customer receives, and not how the service provider delivers that service.

SLAs commonly include segments to address: a definition of services, performance

measurement, problem management, customer duties, warranties, disaster recovery, termination

of agreement.

SLAs have been used since late 1980s by fixed line telecom operators as part of their contracts

with their corporate customers. This practice has spread such that now it is common for a

customer to engage a service provider by including a service level agreement in a wide range of

service contracts in practically all industries and markets. Internal departments (such as IT, HR,

and real estate) in larger organizations have adopted the idea of using service-level agreements

with their "internal" customers — users in other departments within the same organization. One

benefit of this can be to enable the quality of service to be benchmarked with that agreed to

across multiple locations or between different business units. This internal benchmarking can

also be used to market test and provide a value comparison between an in-house department and

an external service provider.

Service level agreements are, by their nature, "output" based – the result of the service as

received by the customer is the subject of the "agreement." The (expert) service provider can

demonstrate their value by organizing themselves with ingenuity, capability, and knowledge to

deliver the service required, perhaps in an innovative way. Organizations can also specify the

way the service is to be delivered, through a specification (a service level specification) and

using subordinate "objectives" other than those related to the level of service. This type of

agreement is known as an "input" SLA. This latter type of requirement is becoming obsolete as

organizations become more demanding and shift the delivery methodology risk on to the service

provider.

Service level agreements at different levels

SLAs are also defined at different levels:

Customer-based SLA: An agreement with an individual customer group, covering all the

services they use. For example, an SLA between a supplier (IT service provider) and the

finance department of a large organization for the services such as finance system, payroll

system, billing system, procurement/purchase system, etc.

Service-based SLA: An agreement for all customers using the services being delivered by

the service provider. For example:

A car service station offers a routine service to all the customers and offers certain

maintenance as a part of offer with the universal charging.

A mobile service provider offers a routine service to all the customers and offers certain

maintenance as a part of offer with the universal charging

An email system for the entire organization. There are chances of difficulties arising in

this type of SLA as level of the services being offered may vary for different customers

(for example, head office staff may use high-speed LAN connections while local offices

may have to use a lower speed leased line).

Multilevel SLA: The SLA is split into the different levels, each addressing different set of

customers for the same services, in the same SLA.

Corporate-level SLA: Covering all the generic service level management (often abbreviated

as SLM) issues appropriate to every customer throughout the organization. These issues are

likely to be less volatile and so updates (SLA reviews) are less frequently required.

Customer-level SLA: covering all SLM issues relevant to the particular customer group,

regardless of the services being used.

Service-level SLA: covering all SLM issue relevant to the specific services, in relation to

this specific customer group.

Common metrics

Service level agreements can contain numerous service performance metrics with

corresponding service level objectives. A common case in IT service management is a call

center or service desk. Metrics commonly agreed to in these cases include:

ABA (Abandonment Rate): Percentage of calls abandoned while waiting to be answered.

ASA (Average Speed to Answer): Average time (usually in seconds) it takes for a call to be

answered by the service desk.

TSF (Time Service Factor): Percentage of calls answered within a definite timeframe, e.g.,

80% in 20 seconds.

FCR (First-Call Resolution): Percentage of incoming calls that can be resolved without the

use of a callback or without having the caller call back the helpdesk to finish resolving the

case.

TAT (Turn-Around Time): Time taken to complete a certain task.

Uptime is also a common metric, often used for data services such as shared hosting, virtual

private servers and dedicated servers. Common agreements include percentage of network

uptime, power uptime, number of scheduled maintenance windows, etc.

Many SLAs track to the Information Technology Infrastructure Library specifications when

applied to IT services.

Outsourcing

Outsourcing involves transfer of responsibility from an organization to a supplier. The

management of this new arrangement is through a contract that may include a service level

agreement. The contract may involve financial penalties and the right to terminate if SLAs

metrics are consistently missed. Setting, tracking, and managing SLAs is an important part of

the outsourcing relationship management(ORM) discipline. It is typical that specific SLAs are

negotiated up front as part of the outsourcing contract, and they are utilized as one of the primary

tools of outsourcing governance.

6. Case Study: Information system in a restaurant.

Ans.

Case Study on MIS: Information System in Restaurant

Case Summary:

A waiter takes an order at a table, and then enters it online via one of the six terminals located in the restaurant dining room. The order is routed to a printer in the appropriate preparation area: the cold item printer if it is a salad, the hot-item printer if it is a hot sandwich or the bar printer if it is a drink. A customer’s meal check-listing (bill) the items ordered and the respective prices are automatically generated. This ordering system eliminates the old three-carbon-copy guest check system as well as any problems caused by a waiter’s handwriting. When the kitchen runs out of a food item, the cooks send out an ‘out of stock’ message, which will be displayed on the dining room terminals when waiters try to order that item. This gives the waiters faster feedback, enabling them to give better service to the customers. Other system features aid management in the planning and control of their restaurant business. The system provides up-to-the-minute information on the food items ordered and breaks out percentages showing sales of each item versus total sales. This helps management plan menus according to customers’ tastes. The system also compares the weekly sales totals versus food costs, allowing planning for tighter cost controls. In addition, whenever an order is voided, the reasons for the void are keyed in. This may help later in management decisions, especially if the voids consistently related to food or service. Acceptance of the system by the users is exceptionally high since the waiters and waitresses were involved in the selection and design process. All potential users were asked to give their impressions and ideas about the various systems available before one was chosen.

Questions:

In the light of the system, describe the decisions to be made in the area of strategic planning, managerial control and operational control? What information would you require to make such decisions?

What would make the system a more complete MIS rather than just doing transaction processing?

Explain the probable effects that making the system more formal would have on the customers and the management.

Solution:

1. A management information system (MIS) is an organized combination of people,     hardware, communication networks and data sources that collects, transforms and distributes information in an organization. An MIS helps decision making by providing timely, relevant and accurate information to managers. The physical components of an MIS include hardware, software, database, personnel and procedures.

Management information is an important input for efficient performance of various managerial functions at different organization levels. The information system facilitates decision making. Management functions include planning, controlling and decision making. Decision making is the core of management and aims at selecting the best alternative to achieve an objective. The decisions may be strategic, tactical or technical. Strategic decisions are characterized by uncertainty. They are future oriented and relate directly to planning activity. Tactical decisions cover both planning and controlling. Technical decisions pertain to implementation of specific tasks through appropriate technology. Sales region analysis, cost analysis, annual budgeting, and relocation analysis are examples of decision-support systems and management information systems.

There are 3 areas in the organization. They are strategic, managerial and operational control.

Strategic decisions are characterized by uncertainty. The decisions to be made in the area of strategic planning are future oriented and relate directly to planning activity. Here basically planning for future that is budgets, target markets, policies, objectives etc. is done. This is basically a top level where up-to-the minute information on the food items ordered and breaks out percentages showing sales of each item versus total sales is provided. The top level where strategic planning is done compares the weekly sales totals versus food costs, allowing planning for tighter cost controls. Executive support systems function at the strategic level, support unstructured decision making, and use advanced graphics and communications. Examples of executive support systems include sales trend forecasting, budget forecasting, operating plan development, budget forecasting, profit planning, and manpower planning.

The decisions to be made in the area of managerial control are largely dependent upon the information available to the decision makers. It is basically a middle level where planning of menus is done and whenever an order is voided, the reasons for the void are keyed in which later helps in management decisions, especially if the voids are related to food or service. The managerial control that is middle level also gets customer feedback and is responsible for customer satisfaction.

The decisions to be made in the area of operational control pertain to implementation of specific tasks through appropriate technology. This is basically a lower level where the waiter takes the order and enters it online via one of the six terminals located in the restaurant dining room and the order is routed to a printer in the appropriate preparation area. The item’s ordered list and the

respective prices are automatically generated. The cooks send ‘out of stock’ message when the kitchen runs out of a food item, which is basically displayed on the dining room terminals when waiter tries to order that item. This basically gives the waiters faster feedback, enabling them to give better service to the customers. Transaction processing systems function at the operational level of the organization. Examples of transaction processing systems include order tracking, order processing, machine control, plant scheduling, compensation, and securities trading.

The information required to make such decision must be such that it highlights the trouble spots and shows the interconnections with the other functions. It must summarize all information relating to the span of control of the manager. The information required to make these decisions can be strategic, tactical or operational information.

Advantages of an online computer system:

Eliminates carbon copies

Waiters’ handwriting issues

Out-of-stock message

Faster feedback, helps waiters to service the customers

Advantages to management:

Sales figures and percentages item-wise

Helps in planning the menu

Cost accounting details

2. If the management provides sufficient incentive for efficiency and results to their customers, it would make the system a more complete MIS and so the MIS should support this culture by providing such information which will aid the promotion of efficiency in the management services and operational system. It is also necessary to study the keys to successful Executive Information System (EIS) development and operation. Decision support systems would also make the system a complete MIS as it constitutes a class of computer-based information systems including knowledge-based systems that support decision-making activities. DSSs serve the management level of the organization and help to take decisions, which may be rapidly changing and not easily specified in advance.

Improving personal efficiency, expediting problem solving (speed up the progress of problems solving in an organization), facilitating interpersonal communication, promoting learning and training, increasing organizational control, generating new evidence in support of a decision, creating a competitive advantage over competition, encouraging exploration and discovery on the part of the decision maker, revealing new approaches to thinking about the problem space

and helping automate the managerial processes would make the system a complete MIS rather than just doing transaction processing.

3.  The management system should be an open system and MIS should be so designed that it highlights the critical business, operational, technological and environmental changes to the concerned level in the management, so that the action can be taken to correct the situation. To make the system a success, knowledge will have to be formalized so that machines worldwide have a shared and common understanding of the information provided. The systems developed will have to be able to handle enormous amounts of information very fast.

An organization operates in an ever-increasing competitive, global environment. Operating in a global environment requires an organization to focus on the efficient execution of its processes, customer service, and speed to market. To accomplish these goals, the organization must exchange valuable information across different functions, levels, and business units. By making the system more formal, the organization can more efficiently exchange information among its functional areas, business units, suppliers, and customers.

As the transactions are taking place every day, the system stores all the data which can be used later on when the hotel is in need of some financial help from financial institutes or banks. As the inventory is always entered into the system, any frauds can be easily taken care of and if anything goes missing then it can be detected through the system.

THANK YOU