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Management Information System Unit 8

Sikkim Manipal University Page No. 149

Unit 8 Trends in MIS

Structure:

8.1 Introduction

Objectives

8.2 Recent Trends in MIS

Introduction to Decision Support Systems (DSS)

DSS components

Model of DSS

Present status of MIS in organisations

Importance of MIS in organisations

8.3 Artificial Intelligence (AI)

Introduction to Artificial Intelligence (AI)

Introduction to Neural Networks (NN)

Artificial intelligence and neural networks

Introduction to Expert Systems (ES)

Expert systems structure

Differences between DSS and ES

Business applications

8.4 Online Analytical Processing (OLAP)

8.5 Open Source Software

8.6 Software as a Service (SaaS)

8.7 Summary

8.8 Glossary

8.9 Terminal Questions

8.10 Answers

8.11 Case Study

8.1 Introduction

In the earlier unit, you have learnt about the enterprise business systems in

detail. In this unit, you will learn about the trends in MIS that prevail in

organisations. For the last few decades MIS is perceived by different peoplein various organisations in diverse views. This is because the MIS has been

evolving in a variety of forms under different levels of management. Some of

the developments are recent additions and some are still in the development

stage.

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Objectives:

After studying this unit, you should be able to: explain the recent trends in MIS

analyse decision support systems and its components

describe expert systems and its structure

analyse artificial intelligence and neural networks

8.2 Recent Trends in MIS

Information technology has grown as a powerful tool and is omnipresent in a

business enterprise. Old traditional MIS tools and techniques are displaced

by new set of software. Let us now learn about the various MIS currently

used in business.

8.2.1 Introduction to Decision Support Systems (DSS)

Decision Support System (DSS) is an interactive, flexible, computer based

information system. It uses rules and models for processing data to support

various managerial levels, ranging from top executives to managers in their

decision making. It supports all phases of decision making such as

intelligence, design, choice and implementation.

DSS is usually built to support the solution of a certain problem and it does

not replace the decision maker. It is user-friendly with strong graphical

capabilities.

8.2.2 DSS components

The components of a DSS include a database for query and analysis,

software with models, data mining and other analytical tools and a user

interface. The DSS database is a collection of current or historical data from

a number of applications or groups. It can be a small database or a

massive date warehouse. The DSS software system includes software tools

for data analysis. They contain various Online Analytical Processing

(OLAP) tools, data mining tools or a collection of mathematical and

analytical models. A model can be a physical model, a mathematical model

or a verbal model. Most commonly used are the statistical functions such as

means, medians, deviations and scatter plots. Optimisation models, such as

linear programming are used to determine optimal resource allocation.

Figure given below depicts the components of a DSS.

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8.2.5 Importance of MIS in organisations

Many organisations in the world make use of MIS as it plays an important

role in every business towards its growth. It is used as a tool in management

to perform a SWOT (Strength, Weakness, Opportunity, and Threat)

analysis, etc., to find facts about the organisation.

Let us see the importance of MIS

It helps and provides facts of data in decision making.

It provides some alternatives by which the management can come to a

decision on various issues. From the available alternatives a best

alternative can be chosen to obtain a desired result.

Lateral communication in the organisation is generally increased by the

use of MIS.

MIS helps in planning, organising, controlling and directing the activitiesof the organisation.

The management, on the basis of the MIS reports compare the past and

present data to take informed decisions.

These types of data in MIS are used to apply for an effective controlling

of measures.

MIS supports decentralisation of the organisation. Through

decentralising activities the management is able to approach the lower

level of employees.

1. Contribution of new trends

As information technology has grown more powerful and ubiquitous inbusiness settings, the role of the traditional MIS has been discarded after

the arrival of new software applications.

A trend replacing conventional MIS since the 1980s has been the adoption

of Executive Information Systems (EISs) and other high-level decision

support systems. EISs are designed for top executives to gather important

information from all major business systems such as finance, inventory,

payroll, etc. and process it in very sophisticated ways and possibly even

integrate it with outside data such as competitive intelligence or industry

statistical norms. By providing such highly refined control over strategic

information, EISs have slowly lost their importance because the MIS

provides more routine kinds of analyses.

2. Networking capability

Another trend in MIS is the ability for companies to network with other

companies for business purposes. Manufacturing firms can shorten their

supply chain using Electronic Data Interchange (EDI) to transfer the

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necessary information for ordering more products. Networking also allows

companies to transfer money through several bank accounts, creating a

quicker process for paying bills and purchasing materials. An MIS ensures

that management has all the required information on the business

operations and allows them to review the effectiveness of operations.

3. Data mining tools

An important trend in MIS is the ability of companies and other organisations

to use data mining tools to find patterns in consumer purchases and other

business trends. This allows management to translate the information into

goals and directions for future business operations. Most MIS software

contain trending or forecasting models that allow companies to project

emerging consumer markets for profitable operations. Companies can use

their internal figures in the MIS to measure the effectives of their externaldata mining techniques.

Example I:

Population of Delhi, India: This shows the projected population of Delhi in

2011.

Table 8.1: Projected Population Characteristics as on 1st March 2001 - 2026

Indicator 2001 2006 2011 2016 2021 2026

i) Population in (000)

Total 13851 16021 18451 21285 24485 27982

Male 7607 8835 10215 11827 13650 15645

Female 6243 7186 8235 9458 10835 12337Sex ratio 821 813 806 800 794 789

Density persq Km

9340 10803 12441 14353 16511 18868

ii) Age group in (000)

age18 above 8466 10551 12876 15346 17891 20530

Age 0 to 14 age 4500 4450 4514 4848 5548 6248

Age 15 to 59 8651 10662 12744 14847 16804 18929

Age 60 plus 700 909 1193 1589 2131 2805

iii) % of population

Age 0 to 14 32.5 27.8 24.5 22.8 22.7 22.3

Age 15 to 59 62.5 66.5 69.1 69.8 68.6 67.6

Age 60plus 5.1 5.7 6.5 7.5 8.7 10.0

Age 15to 49 female 55.6 59.2 61.1 61.1 59.3 58.0

Source: Population projection (Trend) by Govt. of India

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As depicted in table 8.1, the density of population per square kilometre

increases to 18868, almost double the population of the year 2001.The MIS states the growing trend of the population. Therefore, the

government can use the above data to take necessary control measures to

reduce the population.

Example II

Trends in Indian banking industry

Jyothi Kumar Pandey, (College of Agricultural Banking, Reserve Bank of

India, Pune, indicated that there are several road blocks to creativity in

banking industry and the only way is to move towards technology and

electronic clearing environment in banking industry. The banking industrywill stand to gain

Recognition Automation

Improve telecom networks

Rapid restructuring programmes.

After the successful implementation of MIS in the banking sector:

There is successful transformation to a sales culture:

o Branches of banks are called as stores.

Stresses on the employees of banks to focus on sales at all levels.

o Focus on customer experience:

Friendly banker with a service motive.

o Shift from brick to mortar to high level of web and Internet banking

system including mobile banking.

Brick and mortar refers to the type of business where business is physically

and practically done in a stores, etc. Wherein anyone can go in see, touch

and test articles for its working condition so as to purchase them from these

shop keepers. In general this term is used for businesses where products

are sold in physical locations. In the case of dotcom businesses is done

through a mail order.

Other trends

More stress on e-money, plastic money and Internet based delivery

channel.

Lower credit to manufacturing and productive sectors.

Higher growth in housing and auto finance.

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2. The Transaction Processing System (TPS) is a collection of

current or historical data from a number of applications or groups.(True/False)

3. Manufacturing firms can shorten their supply chain using electronic

data ________________.

4. __________, such as linear programming are used to determine

optimal resource allocation.

5. The _____ database is a collection of current or historical data from a

number of applications or groups

8.3 Artificial Intelligence (AI)

In the previous section, you learnt the recent trends in MIS. You will nowlearn about Artificial Intelligence. Artificial Intelligence (AI) is the skill and

engineering which includes several scientific mathematical functions to

formulate an organisational system that can conceive and discharge work

like a human being. Let us discuss AI for our basic understanding.

8.3.1 Introduction to Artificial Intelligence (AI)

AI can understand, examine and resolve problems. Such a system that uses

the ingredients artificially is known as artificial intelligent systems. The

artificial intelligence system functions like a human being and helps a

manager in taking quick decisions.

Software developed for AI is created using computer language like Prolog,

C++, Java, LISP, etc. To develop an AI for business application the concept

of fuzzy logic is used. With regard to business problems related to finance

applications apart from fuzzy logic concepts, two other concepts of AI

namely genetic algorithm and chaotic models are used.

8.3.2 Introduction to Neural Networks (NN)

Neural Networks (NN) is modelled on the basis of the neuron structure of

the human brain.

Neuron is a micro cell which is connected to thousands of other micro cells

in the brain. It is a system which tries to learn from the database and the

manager then decides as to what the right answer is. The entire neural

network is realised in the form of software. The software renders the

computer as a problem solver.

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The neural networks build strong databases for problem solving depending

upon the decisions taken by the manager in the form of responseconfirmation given to the system. Neural networks can be used in various

business applications like forecasting, stock analysis, market analysis etc.

Advantages of neural networks

Neural networks are used to forecast some complex data patterns. When

designed properly, they can be used as experts for a particular project. They

have the ability to adjust to the changing environment and thus are very

flexible. For example, it can forecast net asset values of mutual funds with

40% accuracy. They take into account all variables and relationships

between the data and detect patterns and trends in any set of data.

Disadvantages of neural networks

The process of designing the neural networks is very complex and time

consuming. The network needs to be trained continuously with different sets

of data. In the training phase, large volumes of examples are used. Without

repeated training the accuracy of the network will decline. Over-training with

large amounts of data also leads to inaccuracy. Sometimes, there is

instability in problem solving. With the data constantly changing, it is difficult

to repeat a solution to a problem and explain how it arrived at that solution.

Neural networks results are often criticised because of the fact that it is

unable to give justification of how a particular solution has been arrived at.

The rules are completely not understood.

8.3.3 Artificial intelligence and neural networks

Artificial intelligence is an area of science and technology based on fields

that come under computer science, biology, psychology, linguistics,

mathematics and engineering. The aim of AI is to promote computers that

can simulate the ability to think, see, hear, walk, talk and feel. In other

words, simulation of computer functions normally is linked with human

intelligence, such as logical thinking, finding out reasons and solving

troubles.

AI can be grouped under three major areas namely cognitive science,robotics and natural interfaces. Cognitive science focuses on researching on

how the human brain does work and how human beings imagine and find

out. Applications in the cognitive science area of AI include the exploitation

of proficient systems and other knowledge-oriented systems that add a

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knowledge base and some reasoning capacity to information systems. Also,

included are accommodative learning systems that modify their activitybased on information it posses as it operates. Chess-playing methods are

some examples of such systems.

Fuzzy logic systems can process data that are fractional or equivocal. Thus,

they solve semi-structured problems with partial knowledge by developing

estimated inferences and answers, as done by humans.

Neural network software can learn by treating sample problems and their

solutions. As neural networks begin to distinguish designs, they can start

programming themselves to solve such problems on their own.

Neural networks are computing systems that are similar to human brainswhich are interconnected through neurons. The neurons are called as brain

cells. The human brain is estimated to have over 100 billion neuron brain

cells. The neural networks are lot simpler in architecture. Like the brain, the

neutral network operates through coordinated processors in parallel and

dynamically with one another.

This helps the network to operate and learn from the data it processes,

similar to the human brain. The network distinguishes patterns and

relationships in the data. Hence, as and when more data and examples are

received as input, the better it can learn to replicate the results of the

examples it processes. It is now clear that, the neural networks can changethe strengths of the links between the processing elements in response to

changing patterns in the data it receives and results that occur.

Genetic algorithm software uses Darwinian principle (survival of the fittest),

randomising and other mathematics functions to imitate evolutionary

processes that can generate increasingly better solutions to problems.

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Figure 8.4 depicts few applications of AI.

Expert systems Visual perception Natural languagesLearning systems Tactility Speech recognitionFuzzy logic Dexterity Multi-sensory interfacesGenetic algorithms Locomotion Virtual realityNeural networks NavigationIntelligent agents

Fig. 8.4: Applications of AI

Cognitive Science

Cognitive science is nothing but the mental representations correspondent

to computer data structures, and computational processes similar to

computational algorithms.

Robotics: Engineering and physiology are the basic subjects of robotics.

Robotic machines are produced using robotic applications along with

computer intelligence and physical movements are controlled by computers.

The robotic applications are developed in such a way to give power to robot

to view, feel and physical movement. The robotic application also enables

the robot to walk in any terrain and helps the robot to navigate and reach the

destination correctly.

Natural interfaces: The development of natural interfaces is indispensable

to the use of computers by people. Development of normal languages and

speech recognition are major thrusts in this area of AI. The goal of the AI

research is to make the computers and robots to talk and understand each

other through conversational language as practised by human beings. Other

natural interface research applications include the development of multi-

sensory devices that utilise the body movements to control computers. This

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reliability and faster response time. It helps to solve complex problems with

in a small domain.It is capable of analysing the problem and can construct a business model

appropriate to the characteristics of the application. Based on the model

necessary objectives and constraints are identified. It identifies appropriate

tools to solve the model. It uses the tools to solve the problem sensitivity

analysis.

Self Assessment Questions

6. _________ is the skill and engineering which includes several scientific

mathematical functions to formulate an organisational system that can

conceive and discharge work like a human being

7. A _______ is a micro cell which is connected to thousands of other

micro cells in the brain.

8. The goal of AI is to develop computers that can ________ the ability to

think, see, hear, walk, talk and feel.

9. The components of an ________ system include software modules and

knowledge base.

Activity 1:

Try to construct a model of a Robot -person and list out what are required

to make him artificial intelligent..

8.4 Online Analytical Processing (OLAP)

In the previous section you have learnt about artificial intelligence. In this

unit you will learn about another MIS trend of Online Analytical Processing

(OLAP).

OLAP allows managers to find patterns, trends and exceptions in large

amount of data from different angles in real time. It involves three analytical

procedures of consolidation, drill down and slicing and dicing.

Consolidation

Inter-related data is grouped according to requirement. This allows the data

to be rolled up to a higher level. For example, it allows the individual sales

representative data to be rolled up to the branch level, branch level data to

be rolled up to the city level and so on.

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Drill down

This operation is the reverse of the consolidation process and allows themanager to look into the particulars. That is the data from the higher level

can be expanded to view the lower level data. For example, city level sales

data can be drilled down to the branch sales data and branch data to

individual sales representative data.

Slicing and Dicing

This operation allows the data to be viewed from different angles based on

time. One slice may show regional sales, another slice sales channel sales

and on. This operation is executed along a time axis to expose trends in

data.


10. _________ OLAP operation allows the data to be viewed from different

angles based on time.

11. _________OLAP operation is the reverse of the consolidation process

and allows the manager to look into the particulars.

8.5 Open Source Software

Open Source software refers to applications that are distributed along with

their source code. This enables the users to modify the working ofapplication to suit their needs. Users can give the software to others under

the original license. Also the license is free from technology or interface

restriction. The users of such applications can be organisations,

professionals or home users. The open source code is distributed free or for

payment. For example instead of using Microsoft Office Suite organisations

can download OpenOffice.org suite free of cost from the internet.

Open source models in use

Currently there are three models in use

Sponsored open source

Not for profit organisations maintain and organize the development of open

source software. For example Mozilla foundation supports the development

of Firefox web browser. Likewise Oracle distributes OpenOffice.Org suite

with source code.

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Open Source Service

The creator of Linux operating system Linus Torvalds distributed the sourcecode of the operating system to all who were interested in upgrading the

same. This led to the open service model. Even today Linux operating

system license is free but companies like Red Hat Inc charge for installation,

support and training.

Well known companies like Novell, HP and Unisys participate in this

marketplace by distributing open source software like MySql (database

management system), Apache Web server and Linux operating system.

Professional Open Source

A group of professionals like software developers, testers, programmers and

adopters work together to create open source software. They depend on

their understanding of the source code to provide software to the customer

for their requirements.

Advantages of open source

In comparison to proprietary software like Microsoft Windows the open

source software like Linux operating system is crash proof and

consistent. Also the switching costs are lower as customers can modify

code to suit their needs.

It exploits the power of disparate software professional situated all over

the world to create powerful software. There is no legal constraint on the number of simultaneous users when

setting up and using open source software

Most of the open source software is distributed free of cost.


12. __________ software refers to applications that are distributed along

with their source code.

13. There is legal constraint on the number of simultaneous users when

setting up and using open source software(True/False)

8.6 Software as a Service (SaaS)

SaaS is software delivery model where the application including database is

installed on the data centre owned by the service providers .Multiple entities

access the application interface on the web. The plus point for organisations

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using this service is that the organisation need not invest in IT and own the

application but use the internet to access the software. Also the paymentcould be in terms of pay per use or subscription or flat licensing fee. The

organisation need not employ IS personnel to troubleshoot and maintain the

system. The service providers do this.

SaaS software ranges from simple free service like email (Gmail, yahoo),

Google analytics and Google labs to complex enterprise systems like

Infosys banking solution software Finnacle and Salesforce.coms SaaS

ERP.

The disadvantage of SaaS is that it is dependent on the Internet and the

service provider. If internet gets disconnected then the application cannot be

used. For example internet service providers like Airtel and BSNL send

messages to inform customers that internet services may be disrupted for

some hours due to maintenance activity. Also if service provider has some

problems at the data centre then the services may not be accessible. For

example Salesforce.com a well known SaaS provider experienced this

problem that resulted in its customer losing sales during the Christmas

season.


14. If internet gets disconnected then the SaaS application cannot be used.

(True/False)

15. SaaS is software delivery model where the application including

database is installed on the organizations computers and servers.

(True/False)

8.7 Summary

Let us recapitulate the important concepts discussed in this unit

Information technology is omnipresent in a business enterprise.

Artificial Intelligence is the science and technology based on various

functions to develop a system that can think and work like a humanbeing

NN is modeled on the basis of the neuron structure of the human brain.

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An important trend in MIS is the ability for companies and other

organisations to use data mining tools to collect information regardingconsumer purchases and other economic trends

Expert systems help diagnose illness, search minerals, analyse

compounds, recommend repairs and do financial planning.

By integrating DSS and ES, it is possible the blend their advantages and

derive the best out of them.

OLAP allows managers to find patterns, trends and exceptions in large

amount of data from different angles in real time. It involves three

analytical procedures of consolidation, drill down and slicing and dicing.

Open Source software refers to applications that are distributed along

with their source code. This enables the users to modify the working ofapplication to suit their needs.

SaaS is software delivery model where the application including

database is installed on the data centre owned by the service providers

and multiple entities access the application interface on the web.

8.8 Glossary

Analyt ical model: A computer based mathematical model created to

explore business alternatives.

Source Code:Instructions written for the software in a programming

language like Java and Visual Basic.

Switch ing Cost : Cost in terms of cash, effort, hassles and time taken for a

customer to change over to competitors products and services

8.9 Terminal Questions

1. Explain the decision support systems in detail.

2. What is artificial intelligence? How is it different from neural networks?

3. How can expert systems be useful in MIS and management decision

making process?

4. What are the differences between DSS and ES?

5. Describe the three analytical procedures involved in OLAP

6. What is open source software? Discuss the various models.

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8.10 Answers


1. True

2. False

3. Interchange

4. Optimisation

5. DSS

6. Artificial Intelligence

7. Neuron

8. Simulate

9. Expert

10. Slicing and dicing

11. Drill down

12. Open Source

13. False

14. True

15. False

Terminal Questions

1. Decision Support System (DSS) is an interactive, flexible, computer

based information system. For details Refer 8.2.1.

2. Artificial Intelligent can understand, examine and resolve the problems.

For details Refer 8.3.

3. An expert system is a knowledge-based information system that uses its

knowledge about a specific, complex application area to act as an expert

consultant to end users. For details refer 8.3.4 and 8.3.5

4. It is possible to integrate ES with DSS only if we understand their

differences. For more details Refer 8.3.6.

5. It involves three analytical procedures of consolidation, drill down and

slicing and dicing. For more details refer 8.4.

6. Open Source software refers to applications that are distributed along

with their source code. For more details refer 8.5.

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8.11 Case Study

Reserve Bank of India (RBI) determines the Cash Reserve Ratio (CRR) andStatutory Liquidity Ratio (SLR) of banks. RBI also monitors the reserve

requirements of individual banks.

To enable RBI to check on the reserve requirements at large and in

individual banks in particular, RBI relies on the report submitted by individual

banks. The individual banks in turn look upon to their branches to provide

information on demand and term liabilities they hold in their branches.

With the advent of computerisation and introduction of core banking system,

the controlling office of the bank is able to call out accurate and real-time

information on demand and time liabilities the bank holds systemicallywithout having to rely on manual figures. Automation has helped in

achieving speed and accuracy in the process of information gathering. This

has also helped the banks to maintain reserves accurately, thereby saving

huge amount of interest.

Discussion Questions:

1. State one area where core banking system helps in information

gathering.

Hint: Banks are required to submit report to RBI related to information

on lending to different sectors. Banks are able to provide real-time,

accurate figures. They are also able to segregate the dues from

borrowers into different buckets for the purpose of gearing up recovery

in order to avoid an asset becoming a non-performing asset.

References:

Josheph S. J., & Mohapatra, Management Information System in

Knowledge Economy,Prentice Hall.

Laudon K., Laudon, J., & D, R. Management Information System,

Managing the Digital Firm,New Delhi: Pearson Education.

O'Brien J. A., Management Information System, New Delhi: GalkotiaPublications.

O'Brien J. A., Marakas, G. M., & Behl, R. (2010), Management

Information Systems,New Delhi: Tata McGraw Hill.

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Piccoli G. (2008), Information Systems for Managers, Text and Cases.

John Wiley & Sons. Robert S., & Mary, S. Management Information Systems, The Manager's

View.Tata McGraw Hill.

S, S. Management Information Systems,Prentice Hall.

E- Reference:

http://www.ehow.com/about_5623380_trends-management-information-

systems

http://searchcio.techtarget.com/definition/bricks-and-mortar

http://www.phrases.org.uk

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