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1 Joshi Tarunkumar Bhupenrakumar : MBA – SEM 2 – MB0031- SET 1

Question 1:a. Explain the impact of MIS in the area of policeinformation system?

Answer:MIS is an Information system which helps in providing the management of an organization with information which is used by management for decisionmaking.

A management information system (MIS) is a subset of the overall internalcontrols of a business covering the application of people, documents,technologies, and procedures by management accountants to solvingbusiness problems such as costing a product, service or a business-widestrategy. Management information systems are distinct from regularinformation systems in that they are used to analyze other informationsystems applied in operational activities in the organization. Academically,the term is commonly used to refer to the group of informationmanagement methods tied to the automation or support of human decisionmaking, e.g. Decision Support Systems, Expert systems, and Executiveinformation systems.

An 'MIS' is a planned system of the collecting, processing, storing anddisseminating data in the form of information needed to carry out the

functions of management. According to Philip Kotler "A marketinginformation system consists of people, equipment, and procedures togather, sort, analyze, evaluate, and distribute needed, timely, and accurateinformation to marketing decision makers."

The terms MIS and information system are often confused. Informationsystems include systems that are not intended for decision making. Thearea of study called MIS is sometimes referred to, in a restrictive sense, asinformation technology management. That area of study should not be

confused with computer science. IT service management is a practitioner-focused discipline. MIS has also some differences with Enterprise ResourcePlanning (ERP) as ERP incorporates elements that are not necessarilyfocused on decision support.

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MIS has a major impact on the functions of any organization. Theorganization derives benefits from the systems in the following form:

a) Speedy access to information,b) Interpretation of data,c) Quick decisions,d) Speedy actions,e) increased productivity and thereby increase in the profitf) Reduced transaction cost.

MIS characteristics

In any organization managers will have varieties of tasks to manage. MIS ismainly designed to take care of the needs of the managers in theorganization.• Organizations will have different departments like marketing, production,sales, inventory, maintenance etc. Each of these departments functionindividually and also in relationship with other departments. Information isavailable in abundance. MIS aids in integrating the information generatedby various departments of the organization.• MIS helps in identifying a proper mechanism of storage of data. The datais maintained in such a way that the unnecessary duplication of data is

avoided.• MIS also helps in establishing mechanism to eliminate redundancies indata. MIS as a system can be broken down into sub systems. Each suchsub system may be programmed. This results in easy access of data,accuracy of data and information. It helps in maintaining the consistency of data.

Function of MIS

The main function of MIS is to help the managers and the executives in theorganization in decision-making.

• Large quantities of data like customers information, competitorsinformation, personnel records, sales data, accounting data etc is collected

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from internal sources like the Company records and external sources likeannual reports and publications. The collected data is organized in the formof a database.• The data from the database is processed and analyzed by using differenttools and techniques.• The results of the analysis are properly presented to the managers tohelp them in decision-making.

Question 1. b. What are the functions and disadvantages of MIS?

Answer:

Advantages and Disadvantages, which we feel, is appropriate in the case.

1) To begin with, in the above Case presentation, the initial paragraph ison the typical work scenario faced by a Manager in most of the servicesector organization. The amount of pressure he is in during his dailyroutines work. Here he seems to be senior most and most computerliterate among others in the office. Hence his boss comes to him and handsover a letter to him, which mentions about Collaboration over Internet. Themanager is supposed to go through the contents and brief everyone by

Thursday. The matter is related to E-Collaboration and E Business. Furtherthere are information on how to get more information on E-Collabration.There are references of various Internet sites given to gather more inputson E-Enterprise, E Business and E Collaboration. E business systems layfoundation of other Enterprise applications, namely E commerce, E-communication and E collaboration.

To understand and discuss about the above terms we need to know thatMIS has been evolving in different forms under different levels of

management. Some of the developments are recent and some are still inthe development stage. The research continues. With the emergence of Internet, business organization has undergone structural, cultural, andqualitatitive change and a new organization structure has emerged which isknown as E business enterprise. In this Enterprise business operations are

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performed through E Communication and E Collaboration initiatives.Therefore, E business enterprise has a global market, reach, source andglobal competition. E business enterprise is more process driven,

technology – enabled and uses its own information and knowledge toperform. It has no geographic boundaries as it can extend its operationswhere Internet works.

About E Collaboration -Every business has a number of work scenarios where group of peoplework together to complete the tasks and to achieve a common objective.The groups could be teams or virtual teams with different memberstrength. They come together to perform a task to achieve some results.The process is called collaboration. The collaboration now is possible withe-technologies, which put these teams in network with Internet support forcommunication, access to different databases and servers. Thesecapabilities help to create collaborative work systems and allow membersto work together cooperatively on projects and assignments.The biggest advantage of E-collaboration is that it taps the collectivewisdom, knowledge and experience of the members. The collaborationteam or group could be within the organisation and between theorganisations as well.

Since, E-collaboration works on an Internet platform and uses webtechnology, work group / team need not be at one physical location. Theycan be at different locations and form a virtual team to work on project orassignment.E-collaboration uses E-communication capabilities to perform collaborativetasks, or project assignment. Its effectiveness is increased by software'GroupWare' that enables the members of the group to share information,invoke an application and work together to create documents and sharethem and so on. GroupWare is collaboration software. E-collaboration helps

work effectively on applications like calendaring and scheduling tasks,event, project management, workflow applications, work groupapplications, document creation and sharing, and knowledge management.

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E-collaboration system components are Internet, Intranet, Extranet andLAN, WAN networks for communication through GroupWare tools,browsers. Application packages are software suit, which help processcustomer requirements. It is supported by databases present on variousservers like mail server, material database, knowledge server, documentserver and so on. 2) MIS for E-business is different compared toconventional MIS design of an organisation. The role of MIS in E-businessorganization is to deal with changes in global market and enterprises. MISproduces more knowledge-based products. Knowledge managementsystem is formally recognized as a part of MIS. It is effectively used forstrategic planning for survival and growth, increase in profit andproductivity and so on.

To achieve the said benefits of E-business organisation, it is necessary toredesign the organisation to realize the benefits of digital firm.The organisation structure should be lean and flat.

2) Get rid of rigid established infrastructure such as branch office or zonaloffice.

3) Allow people to work from anywhere.

4) Automate processes after reengineering the process to cut downprocess cycle time. Make use of groupware technology on Internetplatform for faster response processing.

3) Advantages and Challenges:Internet and networking technology has thrown challenge to enlarge thescope of organisation where customers and vendors become part of theorganisation. This technology offers a solution to communicate, co ordinateand collaborate with customers, vendors and business partners. E-business

enterprise is open twenty-four hours, and being independent, managers,vendors; customers transact business any time from anywhere. It has nogeographic boundaries as it can extend its operations where Internetworks. All this is possible due to Internet and web moving traditional paper

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driven organisation to information driven Internet enabled E-businessenterprise.

MIS in E-organisation deviates from traditional report formats to automatedintelligent knowledge driven system. It enforces manager to act quickly toresponse displayed on the screen. Most of the decisions of middle andoperational management are delegated to IT-enabled information andknowledge driven systems. They are supported by the rule-basedtransaction processing system, decision support systems, expert systems,artificial intelligence (AI) systems, and data warehouse and miningsystems. MIS in E-organisation deviates from the conventional model of 'Capture Compute Process Analyse Report Think and Act' to 'Point Click Respond Act.

Challenges:

One challenge is to convert domestic process design to work forinternational process, where integration of multinational informationsystems using different communication standards, country specificaccounting practices, and laws of security are to be adhered strictly.

This is just not a technical change in business operations but a cultural

change in the mindset of managers and workers to look beyond theconventional organisation. It means changing the organization behaviour totake competitive advantage of the E-business technology.

The last but not the least important is the challenge to organise andimplement information architecture and information technology platforms,considering multiple locations and multiple information needs arising due toglobal operations of the business into a comprehensive MIS.

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Question 2 a. Write a scenario which shows the applications of OLAP systems?

Answer:

A decision support system is a way to model data and make qualitydecisions based upon it. Making the right decision in business is usuallybased on the quality of your data and your ability to sift through andanalyze the data to find trends in which you can create solutions andstrategies for. DSS or decision support systems are usually computerapplications along with a human component that can sift through largeamounts of data and pick between the many choices.

While many people think of decision support systems as a specialized partof a business, most companies have actually integrated this system intotheir day to day operating activities. For instance, many companiesconstantly download and analyze sales data, budget sheets and forecastsand they update their strategy once they analyze and evaluate the currentresults. Decision support systems have a definite structure in businesses,but in reality, the data and decisions that are based on it are fluid andconstantly changing.

Types of DSS

Data-Driven DSSData-Driven DSS take the massive amounts of data available through thecompany's TPS and MIS systems and cull from it useful information whichexecutives can use to make more informed decisions. They don't have tohave a theory or model but can "free-flow" the data. The first generic typeof Decision Support System is a Data- Driven DSS. These systems includefile drawer and management reporting systems, data warehousing and

analysis systems, Executive Information Systems (EIS) and Spatial DecisionSupport Systems. Business Intelligence Systems are also examples of Data-Driven DSS. Data-Driven DSS emphasize access to and manipulation of large databases of structured data and especially a time-series of internalcompany data and sometimes external data. Simple file systems accessed

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by query and retrieval tools provide the most elementary level of functionality. Data warehouse systems that allow the manipulation of databy computerized tools tailored to a specific task and setting or by moregeneral tools and operators provide additional functionality.

Data-Driven DSS with Online Analytical Processing (OLAP) provide thehighest level of functionality and decision support that is linked to analysisof large collections of historical data.

Model-Driven DSS

A second category, Model-Driven DSS, includes systems that useaccounting and financial models, representational models, and optimizationmodels. Model-Driven DSS emphasize access to and manipulation of amodel. Simple statistical and analytical tools provide the most elementarylevel of functionality. Some OLAP systems that allow complex analysis of data may be classified as hybrid DSS systems providing modeling, dataretrieval and data summarization functionality. Model-Driven DSS use dataand parameters provided by decision makers to aid them in analyzing asituation, but they are not usually data intensive. Very large databases areusually not needed for Model-Driven DSS.

Model-Driven DSS were isolated from the main Information Systems of theorganization and were primarily used for the typical "what-if" analysis. Thatis, "What if we increase production of our products and decrease theshipment time?" These systems rely heavily on models to help executivesunderstand the impact of their decisions on the organization, its suppliers,and its customers.

Knowledge-Driven DSS

The terminology for this third generic type of DSS is still evolving.Currently, the best term seems to be Knowledge-Driven DSS. Adding themodifier ―driven‖ to the word knowledge maintains a parallelism in the framework and focuses on the dominant knowledge base component.Knowledge-Driven DSS can suggest or recommend actions to managers.

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These DSS are personal computer systems with specialized problem-solvingexpertise. The "expertise" consists of knowledge about a particular domain,understanding of problems within that domain, and "skill" at solving someof these problems. A related concept is Data Mining. It refers to a class of analytical applications that search for hidden patterns in a database. Datamining is the process of sifting through large amounts of data to producedata content relationships.

Document-Driven DSS

A new type of DSS, a Document-Driven DSS or Knowledge ManagementSystem, is evolving to help managers retrieve and manage unstructureddocuments and Web pages. A Document-Driven DSS integrates a variety of storage and processing technologies to provide complete documentretrieval and analysis. The Web provides access to large documentdatabases including databases of hypertext documents, images, soundsand video.

Examples of documents that would be accessed by a Document-Based DSSare policies and procedures, product specifications, catalogs, and corporatehistorical documents, including minutes of meetings, corporate records,and important correspondence. A search engine is a powerful decision

aiding tool associated with a Document-Driven DSS.

Communications-Driven and Group DSS

Group Decision Support Systems (GDSS) came first, but now a broadercategory of Communications-Driven DSS or groupware can be identified.This fifth generic type of Decision Support System includes communication,collaboration and decision support technologies that do not fit within thoseDSS types identified. Therefore, we need to identify these systems as a

specific category of DSS. A Group DSS is a hybrid Decision Support Systemthat emphasizes both the use of communications and decision models. A Group Decision Support System is an interactive computer-based systemintended to facilitate the solution of problems by decision-makers workingtogether as a group. Groupware supports electronic communication,

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scheduling, document sharing, and other group productivity and decisionsupport enhancing activities We have a number of technologies andcapabilities in this category in the framework – Group DSS, two-wayinteractive video, White Boards, Bulletin Boards, and Email.

Question : 2 b. How does information technology influence theorganisations’s goals.

Answer.:

IT influences Organizations goals

There is always a mention about what IT contributes to corporate strategy.It was recognized that corporation achieved a significant competitiveadvantage by adopting suitable IT concepts in building up their strategy. Itquickly became incumbent on its competitors to neutralize that advantage,and hence to avoid 'competitive disadvantage' (Vitale 1986, Warner 1987,Brousseau 1990). Thebnotion of 'competitive necessity' was created tocomplement that of 'competitive advantage'. Comparison was drawnbetween 'sustainable' and 'contestable' competitive advantage (Clemons1986, Feeny & Ives 1989, Ciborra 1992).

Though many kinds of advantages which can possibly be derived frominnovative use of IT, it is possible to quickly neutralize it by others. A distinction needs to be made between the sustainability of the originaladvantage, and of any derived advantage.

An enhancement to the Porter framework of competitive strategy was thenotion of 'alliance' (Barrett & Konsynski 1982, Gummesson 1987, EDP

Analyzer 1987, Johnston & Vitale 1988, Rockart & Short 1989, Wiseman1989, Konsynski & McFarlan 1990, Ford 1990, Bowersox 1990). This

referred to chains or clusters of organizations which collaborate in order togain competitive advantage over other, similar organizations, or toneutralize the advantage of one or more competitor organizations.

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The innovation in IT and its strategic importance to enterprise iscompatible with the company's existing characteristics and advantages(Beath & Ives 1986, Clemons & Row 1987, Ives & Vitale 1988, Hopper1990). One particularly important facet of this is the notion of 'strategicalignment' of IT policies and initiatives with the directions indicated by thecorporation's senior executives (Henderson & Venkatraman 1989, Earl1989, Broadbent & Weill 1991). An outline of factors that influenceorganization's strategic goals is summarized in the following diagram.

Scott Morton's Five Forces Influencing the Organization’s Objectives

Organizations are facing the re-conceptualization of the role of information

technology in business.

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Q.3 a. Explain the role of systems analyst in SDLC. Explain with a scenario.

Answer:

Software Development Life Cycle (SDLC)India Outsourcing > Software Development Life Cycle

Summary: As in any other engineering discipline, software engineering alsohas some structured models for software development. This document willprovide you with a generic overview about different software developmentmethodologies adopted by contemporary software firms. Read on to knowmore about the Software Development Life Cycle (SDLC) in detail.

Curtain Raiser

Like any other set of engineering products, software products are alsooriented towards the customer. It is either market driven or it drives themarket. Customer Satisfaction was the buzzword of the 80's. CustomerDelight is today's buzzword and Customer Ecstasy is the buzzword of thenew millennium. Products that are not customer or user friendly have noplace in the market although they are engineered using the best

technology. The interface of the product is as crucial as the internaltechnology of the product.

Market Research

A market study is made to identify a potential customer's need. Thisprocess is also known as market research. Here, the already existing needand the possible and potential needs that are available in a segment of thesociety are studied carefully. The market study is done based on a lot of

assumptions. Assumptions are the crucial factors in thedevelopment or inception of a product's development. Unrealisticassumptions can cause a nosedive in the entire venture. Thoughassumptions are abstract, there should be a move to develop tangibleassumptions to come up with a successful product.

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Research and Development

Once the Market Research is carried out, the customer's need is given tothe Research & Development division (R&D) to conceptualize a cost-effective system that could potentially solve the customer's needs in amanner that is better than the one adopted by the competitors at present.Once the conceptual system is developed and tested in a hypotheticalenvironment, the development team takes control of it. The developmentteam adopts one of the software development methodologies that is givenbelow, develops the proposed system, and gives it to the customer.

The Sales & Marketing division starts selling the software to the availablecustomers and simultaneously works to develop a niche segment that couldpotentially buy the software. In addition, the division also passes thefeedback from the customers to the developers and the R&D division tomake possible value additions to the product.

While developing a software, the company outsources the non-coreactivities to other companies who specialize in those activities. Thisaccelerates the software development process largely. Some companieswork on tie-ups to bring out a highly matured product in a short period.

Popular Software Development Models

The following are some basic popular models that are adopted by manysoftware development firms

A. System Development Life Cycle (SDLC) ModelB. Prototyping ModelC. Rapid Application Development Model

D. Component Assembly Model A. System Development Life Cycle (SDLC) Model

This is also known as Classic Life Cycle Model (or) Linear Sequential Model(or) Waterfall Method. This model has the following activities.

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1. System/Information Engineering and Modeling

As software is always of a large system (or business), work begins byestablishing the requirements for all system elements and then allocatingsome subset of these requirements to software. This system view isessential when the software must interface with other elements such ashardware, people and other resources. System is the basic and very criticalrequirement for the existence of software in any entity. So if the system isnot in place, the system should be engineered and put in place. In somecases, to extract the maximum output, the system should be re-engineeredand spruced up. Once the ideal system is engineered or tuned, thedevelopment team studies the software requirement for the system.

2. Software Requirement Analysis

This process is also known as feasibility study. In this phase, thedevelopment team visits the customer and studies their system. Theyinvestigate the need for possible software automation in the given system.By the end of the feasibility study, the team furnishes a document thatholds the different specific recommendations for the candidate system. Italso includes the personnel assignments, costs, project schedule, target

dates etc.... The requirement gathering process is intensified and focussedspecially on software. To understand the nature of the program(s) to bebuilt, the system engineer or "Analyst" must understand the informationdomain for the software, as well as required function, behavior,performance and interfacing. The essential purpose of this phase is to findthe need and to define the problem that needs to be solved .

3. System Analysis and Design

In this phase, the software development process, the software's overallstructure and its nuances are defined. In terms of the client/servertechnology, the number of tiers needed for the package architecture, thedatabase design, the data structure design etc... are all defined in thisphase. A software development model is thus created. Analysis and Design

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are very crucial in the whole development cycle. Any glitch in the designphase could be very expensive to solve in the later stage of the softwaredevelopment. Much care is taken during this phase. The logical system of the product is developed in this phase.

4. Code Generation

The design must be translated into a machine-readable form. The codegeneration step performs this task. If the design is performed in a detailedmanner, code generation can be accomplished without much complication.Programming tools like compilers, interpreters, debuggers etc... are usedto generate the code. Different high level programming languages like C,C++, Pascal, Java are used for coding. With respect to the type of application, the right programming language is chosen.

B. Prototyping Model

This is a cyclic version of the linear model. In this model, once therequirement analysis is done and the design for a prototype is made, thedevelopment process gets started. Once the prototype is created, it isgiven to the customer for evaluation. The customer tests the package andgives his/her feed back to the developer who refines the product according

to the customer's exact expectation. After a finite number of iterations, thefinal software package is given to the customer. In this methodology, thesoftware is evolved as a result of periodic shuttling of information betweenthe customer and developer. This is the most popular development modelin the contemporary IT industry. Most of the successful software productshave been developed using this model - as it is very difficult (even for awhiz kid!) to comprehend all the requirements of a customer in one shot.There are many variations of this model skewed with respect to the projectmanagement styles of the companies. New versions of a software product

evolve as a result of prototyping.

C. Rapid Application Development (RAD) Model

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The RAD models a linear sequential software development process thatemphasizes an extremely short development cycle. The RAD model is a"high speed" adaptation of the linear sequential model in which rapiddevelopment is achieved by using a component-based constructionapproach. Used primarily for information systems applications, the RADapproach encompasses the following phases:

1. Business modeling

The information flow among business functions is modeled in a way thatanswers the following questions:What information drives the business process?What information is generated?Who generates it?Where does the information go?Who processes it?

2. Data modeling

The information flow defined as part of the business modeling phase isrefined into a set of data objects that are needed to support the business.The characteristic (called attributes) of each object is identified and the

relationships between these objects are defined.

3. Process modeling

The data objects defined in the data-modeling phase are transformed toachieve the information flow necessary to implement a business function.Processing the descriptions are created for adding, modifying, deleting, orretrieving a data object.

4. Application generation

The RAD model assumes the use of the RAD tools like VB, VC++, Delphietc... rather than creating software using conventional third generationprogramming languages. The RAD model works to reuse existing program

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components (when possible) or create reusable components (whennecessary). In all cases, automated tools are used to facilitate constructionof the software.

5. Testing and turnover

Since the RAD process emphasizes reuse, many of the programcomponents have already been tested. This minimizesthe testing and development time.

D. Component Assembly Model

Object technologies provide the technical framework for a component-based process model for software engineering.

The object oriented paradigm emphasizes the creation of classes thatencapsulate both data and the algorithm that are used to manipulate thedata. If properly designed and implemented, object oriented classes arereusable across different applications and computer based systemarchitectures. Component Assembly Model leads to software reusability.The integration/assembly of the already existing software componentsaccelerates the development process. Nowadays many component libraries

are available on the Internet. If the right components are chosen, theintegration aspect is made much simpler.

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Question 3. B. Draw a data flow diagram for an hospital managementsystem?

Answer: Diagrams for an hospital management system are as under

Figure 1

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Figure 2

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Figure 3

Figure 4

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Question .4 What is the features contributing to success andfailures of MIS models?

Answer .:Budgeting Models

Controlling the business performance through the budget system is anaccepted management practice.

In this approach, various budgets are prepared, viz., the Sales Budget, theProduction Budget, the Capacity Budget, the Manpower Budget, theExpense Budget, and the Inventory Budget, etc. Using these budgets the

profits are estimated. Budgets are also used for planning and control. Thesystem is used to find out whether the performance is under the budget orover the budget. This gives the manager a self evaluation tool forassessing the current status and also provides some insight into theoperations of the Company.

The use of Spread Sheet, Lotus123, Visicalc, Framework and many othersare a standard tool for these applications, where the planning, budgetingand analysis are required. All these systems are based on the worksheet

which has columns and rows with labels on each. The package helps inarriving at the row totals and the column totals. It not only provides thetotals but also summaries at the subheads.

It has also a facility that if one row or column changes, it computes thechanges in the rest of the worksheet, where it is affected.

Breakeven Analysis Model

This model is simple but very useful for determining the volume of business activity at which there is no loss or profit. The model is used todecide the alternatives based on the cost, volume and price.

BEP= FC___= 100000 = 1000

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REV-VC 200-100WhereFC = Fixed costREV = Revenue per unitBEP = Break Even PointTC = total Cost

VC = Variable CostN = No. of Units demanded

Suppose FC = 1, 00,000, VC/Unit = 100 and Rev = 200 then BEP iscalculated as above.

This model can be built for the company, for the product groups or for anyactivity, where you can identify the fixed cost, the variable cost and therevenue at each activity level in terms of the units demanded. Theadvantage of this model is that it tells you as to what the breakeven pointfor the given level of costs and revenue is. If there are possibilities of altering the costs, it would tell its impact on the breakeven point, i.e., if theprice is reduced, the revenue will come down and the breakeven point willfurther go up. The costs are generally not linear over the entire range of activity. The cost would go up after a breakeven model can be built for themultiple activities and for the nonlinear costs. The computerized model

helps in assessing the various parameters of business and its sensitivitytowards the profit/loss. The model is very popular when the costs areknown and are controllable. It is very handy tool for a quick decision on theprice, cost considerations, etc. and can be used very effectively forcommercial negotiations.

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Question .5 What is the limitations of ERP systems? How do ERPpackages help in overcoming theses limitations?

Answer .:

Limitations of ERP

Success depends on the skill and experience of the workforce, includingtraining about how to make the system work correctly. Many companiescut costs by cutting training budgets. Privately owned small enterprises areoften undercapitalized, meaning their ERP system is often operated bypersonnel with inadequate education in ERP in general, such as APICSfoundations, and in the particular ERP vendor package being used.

· Personnel turnover; Companies can employ new managers lackingeducation in the company's ERP system, proposing changes in businesspractices that are out of synchronization with the best utilization of thecompany's selected ERP.

· Customization of the ERP software is limited. Some customization mayinvolve changing of the ERP software structure which is usually not

allowed.

· Reengineering of business processes to fit the "industry standard"prescribed by the ERP system may lead to a loss of competitive advantage.

· ERP systems can be very expensive to install often ranging from 30,000US Dollars to 500,000,000 US Dollars for multinational companies.

· ERP vendors can charge sums of money for annual license renewal that is

unrelated to the size of the company using the ERP or its profitability.

· Technical support personnel often give replies to callers that areinappropriate for the caller's corporate structure. Computer securityconcerns arise, for example when telling a nonprogrammer how to change

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a database on the fly, at a company that requires an audit trail of changesso as to meet some regulatory standards.

· ERPs are often seen as too rigid and too difficult to adapt to the specificworkflow and business process of some companies —this is cited as oneof the main causes of their failure.

· Systems can be difficult to use.

· Systems are too restrictive and do not allow much flexibility inimplementation and usage.

· The system can suffer from the "weakest link" problem —an inefficiency inone department or at one of the partners may affect other participants.

· Many of the integrated links need high accuracy in other applications towork effectively. A company can achieve minimum standards, then overtime "dirty data" will reduce the reliability of some applications.

· Once a system is established, switching costs are very high for any one of the partners (reducing flexibility and strategic control at the corporatelevel).

· The blurring of company boundaries can cause problems inaccountability, lines of responsibility, and employee morale.

· Resistance in sharing sensitive internal information between departmentscan reduce the effectiveness of the software.

· Some large organizations may have multiple departments with separate,independent resources, missions, chains of command, etc, and

consolidation into a single enterprise may yield limited benefits.

· There are frequent compatibility problems with the various legacysystems of the partners.

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· The system may be over engineered relative to the actual needs of thecustomer.

ERP Integration

Integration is an extremely important part to ERP's. ERP's main goal is tointegrate data and processes from all areas of an organization and unify itfor easy access and work flow. ERP's usually accomplish integration bycreating one single database that employs multiple software modulesproviding different areas of an organization with various business functions.

Although the ideal configuration would be one ERP system for an entireorganization, many larger organizations usually create and ERP system andthen build upon the system and external interface for other stand alonesystems which might be more powerful and perform better in fulfilling anorganizations needs.

Usually this type of configuration can be time consuming and does requirelots of labor hours.

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Question 6. Explain the relationship between artificial intelligenceand neural networks with the help of a scenario?

Answer:

Two factors are necessary for a method to be useful in a variety of countrysettings. An analysis technique to understand information available isrequired that is robust and not constrained. And, data of a comparableformat and scope of measurement is needed to enable parallel analysisacross countries.

Artificial intelligence neural networks and Consumer Confidence Surveys fitthese criteria. This work provides an example of the power of thiscombination.

NEURAL PATTERNS

Marketers constantly face the dilemma of how best to implement a winningstrategy from one market to another.

Thinking globally and acting locally are no longer ideals for internationalmarketers -- rather, thinking globally and acting locally are required for

growth and profit. Differences in consumer perception, spending power,need states, and purchase habits complicate discerning the commonaltieswhich are present. By example we will provide an approach tounderstanding the link between perceptions and spending that can beimplemented in any market. Two factors are necessary for a method to beuseful in a variety of country settings. An analysis technique to understandinformation available is required that is robust and not constrained. And,data of a similar format and scope of measurement will be needed toenable parallel analysis across countries. Artificial intelligence neural

network models continue to provide a new dimension in data analysis formarketers. Because neural nets require no assumptions about a data set’sstructure, distribution, independence or relationship, they are able todiscover patterns present in information that traditional statistical methods

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cannot address. Neural networks use human-like trial and error learningmethods to detect patterns existing within a data set.

Additionally, neural nets have the ability to ignore data that is notsignificant and emphasize that data that is most influential. A neuralnetwork acquires its intelligence by training with a set of variables orfeatures represented by a variety of encoding methods. This knowledge isthen applied as a prediction of the patterns existing in this new datapresented to the network.

Work by Bechtel et al. (1993) provides compelling evidence that consumerconfidence tracking data is a reliable reflection of the macro psychologyattitude-behavior link at the aggregate level of national economicconditions.

Additionally we see confirmation of a strong socio tropic component of consumer confidence that exists across a number of EEC states. Much hasuse has been made of the components of consumer confidence. TheConsumer Confidence Survey of The Conference Board, Inc., New York, isclassified as a leading economic indicator by the U. S. Department of Commerce. This survey is generally referred to as the world’s first and bestknown psychological indicator. According to Bechtel, adaptations of this

index are reported in monthly surveys in each of the twelve nations of theEuropean Economic Community.

Tracking this index and its various components proves beneficial at amacro analytic level. When attempting to use consumer confidence inindustry specific forecasting, the results are less satisfying. Building on thisknowledge, we develop neural networks capable of learning the patterns of change over time in consumer confidence by country.

These patterns are related with sales from a number of major retailcategories, e.g. department stores, automobiles, grocery, food away fromhome, etc. Trained neural net models now generalize this learning andpermit forecasts of consumer category sales in future time as well as innew geographic markets. An example of a model using neural network

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pattern analysis to forecast department store monthly sales is nowpresented.

MODEL STRUCTURE

Guided by Bechtel we are able to construct a parsimonious model. Thismodel is accurate and is of a general structure which may be used in alarge number of individual countries. Of course the model may be refinedfor each country with specific data available in the CCI study.

For this example we use neural pattern analysis to forecast the next monthdepartment store sales (SIC code 531) using current month confidencemeasures. Neural networks such as the one we use here are comprised of a series of layers of neuron processing nodes (Grey- Tedesco, 1991). Onelayer each for input and output. Also a layer of neurons known as thehidden is constructed between the input and output layers. All neurons ineach layer are connected to each neuron in the next layer – input tohidden -- hidden to output. These connections are represented by weightvalues which are modified by the network during the course of training thenetwork. Initially these weights are random numbers; as the neural netexamines each new data record these weights change in order for thenetwork output to more closely match the output of the current data

example. It is the value of these connection weights that depict theknowledge gained by the model. The input vector for the neural network contained a seasonality factor and the monthly Consumer ConfidenceSurvey for the following:

With the exception of the last two items, there are three categories foreach of the above confidence measures.

Therefore, the network input layer contains 26 individual neurons. It is

common with neural networks to have an output vector with more than asingle variable to predict. In this model only one month is estimated. Othermodels using this same confidence survey input are designed to estimateup to three months into the future simultaneously. After pre-processingand design, the neural pattern model appears as follows:

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FULLY CONNECTED NEURAL PATTERN MODEL METHOD AND RESULTS

Monthly data for the period January, 1984 through December, 1994 in theUnited States is used in this model.

Observations are presented to the neural network two at a time. And, thenetwork is permitted to process for 11,000+ iterations through the data.Training is accomplished with approximately 90% of data, while theremaining 10% is withheld for testing the accuracy of the network’sforecasting ability. Using the test data, the model reports a reliability factorof 76% when projecting department store sales two months after thecurrent month’s confidence data, and 89% reliability when forecasting onemonth into the future. We use the term reliability to mean the percentchance of

Business Conditions EvaluationBusiness Conditions ExpectationPersonal Conditions ExpectationsBuying Plans PersonalDepartment Store Sales

All data and weights flow this direction Connection Weights the model

being correct when forecasting sales for a new month. In other words, thisneural pattern model will be correct almost nine out of ten times where itprojects sales for the next one month. Two meaningful uses of any neuralpattern model are: 1) forecasting and 2) the analysis of the relativeimportance of the independent or casual variables. The following tabledisplays the forecast for the last three months of 1994 using this model. allsales in $MM While the accuracy of this model does vary somewhat (2% to6%), its application as a planning tool is a breakthrough is a search forcommonality in quantifying the trends of consumer confidence.

Neural patterns are now available as method for marketers to realize theheretofore untapped information available in a variety of consumerbehavior data. This powerful technology is a bridge for the passage of global marketing strategies. As more data is made available from sources

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through the varied interactive offerings, the ability to glean knowledgefrom this information grows in value. Artificial intelligence neural networkscontinue to offer the greatest opportunity to realize the expectations facingmarketers.

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