MIS Essentials

Dr Sharad L. JoshiProfessor

Vishwakarma Institute of Management, Pune

What is MIS? Study of Information Systems focusing

on their use in Business and Management

MIS combines the theoretical work of computer science, management science and operations research with a practical orientation toward developing system solutions to real life problems and managing information technology resources.

Types of systems Transaction Processing Systems (Dealing with day-

to-day events and actions - Financial Transactions, Student Attendance, Phonecalls, Train Reservation)

Office Automation Systems (Word, Excel) Knowledge Work Systems(Tally, PowerPoint, CAD) Management Info. Systems (Based on TPS – Student

Absenteeism Report, Product-wise Sales, Slow moving items report, Customer Outstandings Report )

Decision Support Systems (Production Scheduling, Data Mining supported analytics)

Executive Support Systems (Dashboards)

M.I.S. Model – applicable to all 6 types of systems

Information

Herbert Simon Model

of Decision Making

Data

Monitoring/Feedback

Processing LogicComputers

Human Beings

Database

Intelligence

Design Choice

Decision Implementation

Performance

Salient Features of Modern MIS Use of Web based GUI’s for acquiring and

displaying data Increasingly faster SQL processors and search

engines to access / explore data Use of graphics and animation in GUI’s Use of multi-layer client–server architecture to

serve large number of users (Client is Front end; server, back end)

Component based software engineering Wide range of software products / packages Use of advanced mining/ analytical tools

Computer capabilities which assist (mainly)in T.P.S.

Capturing Storing Summarizing Arranging Verifying

Retrieving Calculating Reproducing Classifying Communicating

Note : For OAS, KMS, DSS and EIS more sophisticated capabilities of computer are used.

Tools for MIS

On Line Transaction Processing (OLTP)

Relational Data Base Management Internet based, interactive data

capture and query processing Mathematical Models, Business

Analytics

M.I.S. Outputs

OLTP SYSTEM RDBMS

APPLICATIONDEVELOPMENT

SYSTEMS

DATABASE

AccountingApplications

QueryApplications

AnalysisApplications

ControlApplications

Steps in Systems Development for routine M.I.S. Acquiring Data, usually, through an On Line Transaction

Processing System as well as devices such as Bar Code, RFID and Biometric terminals, or off line Data Entry

Placing Data into ‘Tables’ using a Relational Data Base Management System(e.g. ORACLE)

Printing Reports or obtaining Screen Displays using RDBMS features like SQL and DML, mainly for

Accounting Applications Query Applications Analysis Applications Control Applications

Michael Porter on Competitive Advantage Sustainable competitive advantage is achieved

through either or combination of Cost Leadership, Differentiation and Focus.

Specific activities through which a company can create competitive advantage are Inbound Logistics, Operations, Outbound Logistics, Marketing & Sales and Service

Information , used strategically, should assist in achieving superior performance in any of the areas stated above, creating competitive advantage.

How to gain competitive advantage?

I.T. changes the context, creating new opportunities and new threats. Competitive advantage, depends on how well, and how effectively an organization adapts to forces of change.

Explore possibility of re-engineering existing business using IT (like banks and newspapers)

Use information to locate niches, new market segments - geographical, demographical, social etc – use Data Mining

Change structure – e.g. Decentralized to Centralized ( e.g. BOLT in case of shares) or vice versa

Use IT to add value – Better service, less mistakes and earn better prices

Increase efficiency, reduce costs, compete on lower price Enter new markets otherwise inaccessible ( thru eServices)

e.g. Call Center Standardize, Improve control, expand business the way MNC’s

do

MIS and organizational change MIS changes the organizations, by reducing

levels in hierarchy, restructuring flow of work, changing products/ processes, making decisions data-centric (rather than judgmental) and making knowledge more important than seniority.

However, as observed by Levitt, computers alone cannot change the organization. For that to happen, People, Tasks (what to do), Processes (how to do) and Technology have all to change simultaneously.

Classical Model of Decision Making Classical or Economic Model is a Normative

Model (i.e. one stating the norm), based on the following Assumptions.

All alternatives for decision making are known. The decision maker seeks to maximize profit

or utility, where profit motive is not relevant. The decision maker is completely sensitive to

difference between utilities, where relevant.

Administrative Model of Decision Making (Can be also called satisficing or principle of bounded rationality)

Administrative Model is a Descriptive Model based on the assumptions, that the Decision Maker -

Does not know all alternatives for decision making.

Makes a limited search to discover a few satisfactory alternatives.

Makes a Decision which satisfies his or her aspirational level.

Herbert Simon Model of Decision Making – 3 Phases Intelligence phase involves scanning social,

competitive and organizational environment and understanding/ identifying the problem

Design phase involves generating alternatives to solve the problem and evaluating each of the alternatives qualitatively and quantitatively.

Choice phase involves ranking the alternatives based on a variety of criteria and choosing the most suitable among them. Note that the model does not include implementation and feedback, which is said to be its limitation.

Attributes of Information

Timely Availability

Currency (Being Current)

Proper Frequency

Relevance Completenes

s

Consistency Accuracy Reliability Verifiability Clarity Comprehensibi

lty Brevity Cost

Effectiveness

Types of Information Strategic Level – Unstructured, External, Used

for Long Term Planning (Emerging Technologies, Competition, Socio Political Changes etc)

Tactical Level – Semi Structured, Largely Internal, Used for Medium/ Short Term Planning (Customer Perception, Competitors’ Actions, Pricing etc).

Operational Level – Structured, Internal, used for Short Term Planning (Specific Product, Specific Activity, Small Groups etc)

• Information can also be typed (classified) as planning information and control information.

I.T and ITES – Syllabus Topics

Evolution of computers,generations

Tele-communication, Networks IT enabled services such as call

centers, Geographical Information Systems

Example of GIS, indicating influence of political parties in Corporation Elections. The geographical objects and the data is linked thru computer software.

Relational Data Base Management Systems (RDBMS)

RDBMS is a system of inter-related tables, which are used to store the data. The tables are connected to each other thru common fields. The data stored in the tables is accessed thru SQL (Structured Query Language) and DML (Data Manipulation Language).

A RDBMS a table, titled Train Table along with sample entries and a SQL query follows. Train Table is ‘related’ to Reservation Form Table, which also contains Train No.

Despite simple table design, RDBMS is capable of handling millions of records, fast and accurately.

Table Structure – Train Table

Field Name Type Width

TrainNo Number 4

TrainName Text 20

From Text 25

To Text 25

StartTime Number 4

Train Table

TrainNo TrainName From To StartTime

2567Jhelum Express Pune Delhi 1730

2568Krishna Express Hyderabad Bhubaneshwar 1940

2569Udyan Express Bangalore Chennai 730

3456Deccan Queen Pune Mumbai 715

SQL Example from Railway Reservation System Purpose – List trains between Pune and

Delhi Query

select TrainNo, TrainName, StartTimefrom Train_Tablewhere From = ‘Pune’ and To = ‘Delhi’

ResultTrainNo TrainName StartTime2567 Jhelum Express 1730

Data Warehousing and Data Mining (vs Dabases). Data Warehouses are similar to Databases in that both

maintain and access tables – which may contain diverse data like numbers, text, pictures, audio clips, video clips etc.

Data Warehouse has better analysis capabilities (OLAP) while Database has better transaction processing capabilities (OLTP). DB is ‘write-optimized’ ; DW is ‘read-optimized’ . DW is better for analytics. Note that DW and DM handle data in GB and TB.

Data Mining is better designed for quantitative and statistical analysis, whereas DW creates and uses simpler analyses, relying on qualitative interpretation.

All these DB, DW and DM have 5 capabilities – Store, Maintain, Access, Analyze and Present the data.

Decision Support Systems(DSS) and Group Decision Support Systems(GDSS)

Decision Support Systems, in the past were based on low volume of data, and utilized special tools and models (like Linear Programming, Operations Research) for analysis. DSS has now been converted into Business Intelligence, or ‘Analytics’. It uses vast amount of data and analyses it thru sophisticated data warehousing and data mining tools.

Group Decision Support System uses Decision Support System methodology but allows a number of decision makers to work together to arrive at a decision acceptable to the group. One of the techniques used for GDSS is ‘electronic brainstorming’ – brainstorming thru an online chat. A variation of electronic brainstorming called ‘Nominal Group Technique’ , where ideas generated are put to vote and selected, is also used. GDSS is more useful in case of virtual teams.

Business Analytics (DSS) for Godrej Household Products – Sales Force Automation (SFA)

SFA solution was implemented on ‘Tablet’ computing devices with a view to capture transactions related to orders, collection and return of goods electronically and transmit them to the billing system and returns databases.

The tablet computer also displays information about sales history, schemes, promotions and achievement Vs. target of salesmen. It can even suggest an order to the salesman for a particular outlet, based on its past record and current purchase.

IBM XPD Desktop, located at the office, integrates data received thru tablet application with backend billing.

The SFA solution utilizes IBM Business Analytics software.

E (Executive/ Enterprise/ Everybody’s) Information System

E.I.S. started as ‘Executive Information System’, meant for senior executives but is currently used also at other levels where people need to take decisions based on latest and most relevant information. It uses data analysis tools and presentation techniques such as ‘Executive Dashboards’ . Dashboards present information related to Key Result Areas (KRA) or Key Performance Indicators (KPI) in a single screen. Capability to drill down from aggregate data to components is an essential pre-requisite of EIS. Examples of dashboards follow.

Typical Dashboards.

Expert Systems and Artificial Intelligence Expert Systems try to incorporate experts’

knowledge into computer software so as to assist decision making by non-experts (e.g. medical diagnosis, Tax planning). The Expert Systems have ‘knowledge Data Base’ and ‘inference engine’ (i.e. logic) which is used to draw inferences.

Artificial Intelligence ventures into areas which has always required human intelligence. Language Translation and Hand Writing Recognition are two examples. AI uses algorithms similar to human reasoning, so as to assist, if not to take decisions.

Management Issues in MIS (1) – Information Security and Control

External Threats Thru Internet and Thru Remote Access Problems – Hacking, Identity Theft, data loss Firewalls offer a partial solution Internal Threats Password theft, Misuse of authorization, malware (viruses),

physical theft of Hardware and Software Anti Virus Solutions, Access Reviews, Frequent Change of

passwords, back-ups and Business Process Continuity planning, physical controls, maintaining a log of all system activities (audit trails) are the techniques used to combat the threat.

Periodic Information Security Audit is advisable for both.

Management Issues in MIS (2) – Software Quality Assurance

Software quality assurance covers attributes such as reliability, efficiency and promised performance .

In order to assure quality of software, 3 aspects need to be attended to.

1. Creating a quality profile – Specifying qualitative and quantitative aspects of software ( such as number of problems reported, number of updates supplied)

2. Process control thru Requirements, Design, Coding and Testing Checklists , software engineering, Documentation etc.

3. Obtaining third party certification from agencies such as ISO about conformance to quality procedures.

Management Issues in MIS (3) – Ethical Dimensions, Intellectual Property Rights, Global Information Systems

Ethical Aspects are mainly related to misuse of computer technology for personal benefit, intentional manipulation of data, indulging in cybercrime, violating data privacy, even insensitive automation.

Intellectual Property Rights concern software and hardware piracy, violation of patents, breach of trade marks, breach of confidence relating to information held in trust.

Managing Global Information Systems involve dealing with cultural, political and economic challenges posed by different countries, developing appropriate business and IT Strategies for the global marketplace and developing a portfolio of applications to support them.