The document provides information on management information systems (MIS). It defines key terms like data, information, database and file. It describes the stages in converting data to information like capturing, verifying, classifying etc. It discusses classification and types of information. It then introduces MIS, describes its purpose and scope, expectations from MIS and types of MIS reports. The document further discusses functional MIS systems, subsystems and elements of information systems. [END SUMMARY]

1. Management
Information System
Prof. Arathi S. Purohit

2. Basic Terminologies
 Data : Unstructured Raw Facts, Observations
or unevaluated messages.
 Information : Finished Product
 Database : Finished Product laid in a
systematic format.
 File : Logical Existence / name given
 Document : Textual Record

3. Stages in converting
Data to Information
 Capturing
 Verifying
 Classifying
 Arranging / Sorting
 Summarizing
 Calculating
 Storing
 Retrieving
 Reproducing
 Communication

4. Classification of Information
 Action Information : Induces action
 Non – Action Information : Communicates the
status
 Recurring : Regular Information
 Non – Recurring : Non repetitive
 Internal Information
 External Information

5. Types of Information
 Strategic Level
 For strategic decision making one needs strategic
information. It needs more futuristic inputs.
 Tactical Level
 Tactical information used for medium and short
term planning by middle level management.
 Operational Level
 It covers current happenings, information about
specific product or task.

6. Introduction to MIS
An MIS provides managers with information
and support for effective decision making, and
provides feedback on daily operations.
MIS is a system, which makes available the
Right Information to the Right Person at the
Right place at the Right Time in the Right
Form and at Right Cost.

7. Purpose & Scope
The Purpose and Scope of MIS can be defined
as “The combination of human and computer
based resources that results in the collection,
storage, retrieval, communication and use of
data for the purpose of efficient management of
operations and for business planning”.

8. Expectations from MIS
 Handling of Corpus data
 Confirmation of validity of data
 Complex processing through Multi
Dimensional analysis.
 Quick Retrieval
 Mass Storage
 Dynamic
 Timely Communication

9. MIS Reports
 Scheduled reports
Produced periodically, or on a schedule (daily, weekly, monthly)
 Key-indicator report
Summarizes the previous day’s critical activities
Typically available at the beginning of each day
 Demand report
Gives certain information at a manager’s request
 Exception report
Automatically produced when a situation is unusual or requires
management action
 Drill Down Reports
Provide detailed data about a situation.

10. Functional Systems
 Financial MIS
 Manufacturing MIS
 Marketing MIS
 Human Resource MIS
 Accounting MIS
 Geographic information systems

11. Financial Subsystems
 Financial information to all financial
managers within an organization.
 Profit/loss and cost systems
 Auditing
 Internal auditing
 External auditing
 Uses and management of funds

12. Manufacturing Subsystems
 Product Designing
 Production scheduling
 Inventory control
 Manufacturing resource planning (Materials
Requirement Planning with Capacity
Requirements Planning)
 Just-in-time inventory and manufacturing
(Toyota Processing System)
 Process control
 Quality control and testing

13. Marketing Subsystems
 Marketing research
 Product development
 Promotion and advertising
 Product pricing

14. Human Resource Subsystems
 Human resource planning
 Personnel selection and recruiting
 Training and skills inventory
 Scheduling and job placement
 Wage and salary administration

15. Accounting Subsystems
 Detailed information on accounts payable,
accounts receivable, payroll and other petty
expenses.

16. Geographic
Information systems
Capable of assembling, storing, manipulating
and displaying geographically referenced
information.
e.g. Segmentation , Targeting, Water
Consumption Ratio, Property Tax,
GIS Framework
ASK  Acquire  Examine  Analyze  Act

17. GIS Subsystems
 Measure (natural & human made
phenomenon)
 Store (measurements in digital format)
 Analyze (to create more useful information)
 Depict ( in form of maps, graphs, lists)
 Case Study – Role of GIS in NHAI

18. Elements of
Information Systems
 Hardware
 Software
 Data
 People
 Procedures

19. Types of Information Systems
 TPS
 MIS
 DSS
 EIS
 KS
 Note : Basically divided based on Strategic,
Managerial & Operational levels.

20. Evolution of MIS
KS / ES
AI
ESS / EIS
DSS
MIS
OAS
TPS

21. Information as a
Strategic Resource
 Achieving strategic competitiveness in the
present competitive environment could be
enhanced through capturing data, processing
the same, analyzing & transforming into
useable knowledge.

22. Contemporary Approaches
to MIS
 Technical Approach – Based on Operation
Research techniques
 Behavioral Approach – Based on user
requirement/friendliness
 Socio – Technical Approach - Combination

23. Use of Information in
Competitive Advantage
 Due to globalization business environment
have become highly competitive and
information - based. ”Competitive Advantage
is about changing the balance of power
between a firm and its competitors in the
industry, in the firm’s favor”.
Case Study: IS in Restaurant
Case Study: IS in SystemX

24. Porter – Miller
IT affecting competition
 Changes the Industry Structure
 Produces new business
 Creates competitive advantage by giving
companies new ways to out – perform their
rivals.

25. Changes the Industry Structure
 Bargaining power of customers
 Bargaining power of suppliers
 Threat from new entrants in the firm’s market
 Threat from substitute products or services
 Positioning of traditional industry competitors

26. Produces new business
 Information derived from the surveys and the
analysis of the same may lead to birth of a
new business in the existing one. Thus
information confers competitive advantage to
the firm as it can offer a bundle of goods /
services.

27. New ways to out – perform
 Functional Uses
 Strategic Uses

28. Decision Making Models
 Classical Model
 Administrative Models
 Herbert Simon Model
 Rational Decision Making
 Bounded
 Vroom – Jago
 Six Step

29. Classical Model
 Decisions are in Best Interest of its
organization

30. Administrative Model
 Decisions are in Best Interest of the
Manager.

31. Herbert Simon Model
 Phases –
Intelligence
 Intelligence,
 Design,
 Choice
Org
Choice Design

32. Rational Decision Making
 Bounded
 Vroom-Jago
 5 processes and 7 questions
 AutocraticI(A1) – You
 AutocraticII(A2) – team  you
 ConsultativeI(C1) – you – team
 ConsultativeII(C2) – team + you
 GroupII(G2) - team

33. Vroom-Jago
 Do you want High quality solution or best fit
solution?
 Is information gathered sufficient to take your
own decisions?
 Do you have structured problems?
 Do the members agreement towards the
towards is mandatory to accomplish a task?
 Will your group accept your decision?
 Chances of Disagreement from the group
 Goal Congruence (Mgr & Group)

34. Six-Step Model
 Define the problem
 Identify decision criteria
 Weigh the criteria
 Generate alternatives
 Rate each alternative
 Compute the ultimate option

35. Decision Analysis
 What If Analysis
 Sensitivity Analysis
 Goal Seeking Analysis – Goal Seek
 Goal Achieving Analysis - Scenarios

36. Decision Making Tools
 Decision Tree
 Decision Rule
 Decision Table
 Payoff Matrix
 Queuing Models

37. Decision Tree
 Decision Node – Initial Decision Point
 Chance Node – Options generated from
Decision Points

38. Decision Rule
List out all available options

39. Decision Tables
Tables may include both qualitative &
quantitative bases for decisions based on the
decision rules.

40. Payoff Matrix
Is a quantitative technique. It identifies the
degree of likelihood of the occurrence of an
event.
EV – Expected value derived from possible
consequences.
EV= prob (possibility1) + prob(possibility2)

41. Queuing Models
 Queue – Is a line of waiting customers who
require service from one or more service
providers.
 Queuing System – Waiting + Customers +
Service Providers

42. Types of Queues
 Single – Channel, Single – Phase (Clinic)
 Single – Channel, Multiphase (Dual window)
 Multi – Channel, Single – Phase (Bank)
 Multi – Channel, Multiphase (Registration
Process)
 Parallel Single – Phase (Super Markets)
 Customer Discrimination (Insurance Co.)
 Converging Arrivals (Traffic Management)

43. Data Base Management
Systems
DBMS Concepts

44. DBMS Components
 Transaction Management
 Concurrency Control
 Recovery Management
 Security Management
 Language Interface
 Storeage Management
 Database Catalog Management

45. Data Warehouse
 Every organization generates corpus data
from their day-to-day operations. Such data
is considered to be the most powerful asset
of the company.
 The data collected in this way needs to be
only in “update only” format.
 For this activity the organization would
require high end databases.

46. Data Warehouse
Data Warehousing is a new technology that
provides the users the tools to store the
summarized information from multiple, assorted
databases in a single repository.
A Data Warehouse is a
Subject-Oriented,
Integrated,
Time-Varying,
Non-Volatile collection of data.

47. Data Warehouse Structure

48. Data Warehouse Structure
 Data Marts are usually smaller chunks
extracted from Data Warehouse and focus on
a particular subject or department.
 Data Farm is a location all the data storing
servers and other computer systems are
placed.

49. Components/Elements of
Data Warehouse
The major components of a Data Warehouse
are:
Source of Data Warehouse: (Transactional
or Operational Database) from which the data
warehouse is populated.
Processes involved in creating a data
warehouse:
4.A process to extract data from the database,
and bring it to data warehouse.

50. Components/Elements of
Data Warehouse
2. A process to cleanse the data, to ensure its
quality for decision making.
3. A process to load the cleansed data into the
data warehouse database.
4. A process to create any desired summaries
of the data like pre-calculated totals, averages
etc which can be requested often.

51. Components/Elements of
Data Warehouse
Metadata: It is “data about data”.
Query tools: include an end-user interface for
asking questions to the database, in a process
called On-Line-Analytical Processing (OLAP).
They may also include automated tools called
as Data Mining.
Users: Finally, there is User or Users for whom
the data warehouse exists and without whom it
would be useless.

52. Data Warehouse Benefits
 Time
 Quantity & Quality
 Decision Making
 Business Processes
 Business Objectives
Note : Slice and Dice operations

53. Data Warehouse Tools
 Access Tools
 Retrieval Tools
 Database Reporting Tools
 Data Analysis Tools
 Data Mining Tools

54. Data Mining
“Data Mining” or “Knowledge Discovery
Databases (KDD)”, is the non-trivial extraction of
implicit, previously unknown and potentially useful
information from the data.

55. Synonyms of Data Mining
 Knowledge Discovery in Databases (KDD
 Knowledge Extraction
 Data Analysis
 Information Harvesting
 Data Fishing, Data Dredging
 Data Archaeology
 Information Discovery

56. Need of Data Mining
The massive growth of data is due to the wide
availability of data in automated form from
various sources as Web, Business, Research
etc.
We are “Data Rich but Information Poor”
Data is useless, if it cannot deliver knowledge.
That is why data mining is gaining wide
acceptance in today’s world.
Data Mining is likely to emerge as an
important managerial decision making tool.

57. Functioning of Data Mining
The cyclical functioning of Data Mining consists
of the following:
Understand the situation
Building/Developing (suitable) model/s
Undertaking analysis based on the model/s
Initiating appropriate action
Measuring the results
Iterations/Repetition

58. Technologies used in DataMining
 Decision rules
 Decision Trees
 Generic Algorithms
 Non-Linear Regression Methods – Dependencies
are checked
 Case Based Reasoning – Closest past similarities of
the present situation.
 Neural Networks: An Artificial Neural Network (ANN)
is an information processing paradigm that is
inspired by the way biological nervous systems,
such as the brain, process information.

59. Advantages of Neural Networks
 Adaptive learning
 Self-Organization
 Real Time Operation
 Fault Tolerance via Redundant Information
Coding

60. Data Mining Applications
 Marketing
 Finance
 Human Resources / Personnel
 Manufacturing
 Services
 Retail

61. Data Mining – Banking Case
Customers apply for a loan / credit card.
Information such as age, income, employment
history, education, bank accounts, existing
debts etc. is provided.
The bank does further verification and further
decides whether to issue the loan / credit card.

62. Trends affecting Data Mining
Grossman has identified five external trends
which affect Data Mining. They are:
Data Trends - avoid dumping of data.
Hardware Trends – speedy process
Network Trends – New protocols & languages
Scientific Computing Trends - Simulation
Business Trends - predict opportunities and
risks

63. DSS
 DSS are interactive information systems, that
rely on an integrated set of user-friendly
hardware & software tools to produce and
present information that is targeted to support
the management in the decision making
process.

64. Components of DSS
 Database
 Model Base
 Behavioural model
 Trend Analysis, Forecasting
 Management Science Model
 PPM-OB (Budgets)
 Operations Research Model
 Mathematics (MRP)
 DSS Software System

65. Components of DSS Program
Model Base
Model Management
Dialogue Management
Data Management
(DSS Database) (Enterprise Data) (External Data Source)

66. Types of DSS
 Status Inquiry Systems – Searching the
available vendors, products availability,
procurement, stocks
 Data Analysis System – Pricing, Promotional
activities, positioning
 Information Analysis System – selection of
vendor/product/services based on price,
performance, quality etc.
 Accounting Systems – ROI, Payables,
Receivables could be calculated

67. Decision Support Systems
 GDSS – User Interactive computer based
systems which facilitates the solution by set
of decision makers in a group.
 EIS / ESS – It can handle any type of new
situations from which summaries/snapshots
can be generated for assisting the top
management in effective decision-making.
 ES – Expert Systems are computer programs
that represents the knowledge of some
subject specialist with a view to solvig
problems or giving advice.

68. Decision Support Systems
 KBES – Knowledge based expert systems
 AI - Artificial Intelligence is a technology
which helps the application of computers to
the areas that require knowledge, perception,
reasoning, understanding which distinguish
the human behaviour from computers.

69. Issues in MIS
 Security and Control –
 External Threats –
 through internet connection without a firewall.
 Dial-up connections
 Internal Threats
 Passwords
 Employee Discrimination
 Access Ids disclosed to unauthenticated user
 Authorization levels

70. Issues in MIS
 Quality Assurance – Quality indicates the
degree of excellence of a product or service.
 Factors:
 Scale (Measurement Tool), Test (Implement),
Worst (The least acceptable value) , Plan
(Desired Values), Best (Best Fit value that a
system is capable of), Now (the actuals derived)
 Models : Quality Profile Model, Constructive
Quality Model, TickIT Initiative

71. Issues in MIS
 Ethical and Social Dimensions Ethics means
system or code of conduct.
 Ethical & Social Dimension
 Obligation to Management
 Obligation to Society
 Obligation to Employer
 Obligation to Country

72. Issues in MIS
 IPR in IT
Information or related products such as process, code of
conduct, business models, diagrams, layouts can be
classified
as intellectual property which can be viewed, copied &
shared.
In this process it may loose its original identity. Such
information requires protection provisions from:
7. Trade Secrets,
8. Copyright
9. Patents
 Managing Global Information Systems

73. Issues in MIS
 Managing Global Information Systems
 A Global Information Systems architecture consists of
basic information systems required by organizations to
coordinate worldwide trade and other tasks.
 A business driver is an environmental force to which
businesses must respond and that influence a business’s
direction

74. Global Information System

75. Application of MIS
 NHAI
 Hotel Information System
 HRIS
 eHRM
 Applicant Tracking Systems
 SystemX – Budgeting Tools
 ITES