Information Management Unit 5 New IT initiatives

Information Management
Unit 5: New It Initiatives
Prepared and Presented by,
Ganesha Pandian N
1MSM-MBA Even Semester2020

Content
• Role of Information Management in ERP
• E- business
• E- Governance
• Data mining
• Business Intelligence
• Pervasive computing
• Cloud computing
• CMM (Capability Maturity Model)
2MSM-MBA Even Semester2020

ERP – Introduction
• Covers the techniques and concepts employed for the
integrated management of businesses as a whole
• Effective use of management resources
• ERP – technological backbone of e-business, an
enterprise – wide transaction framework with link
into sales order processing, inventory management
and control, production and distribution, planning
and finance”
MSM-MBA Even Semester2020 3

Evolution of ERP
1970 1980 1990 2000 2005
Column1 Column2 Column3
LevelofBusinessIntegration
MRPII
ERP
Extended ERP
ERP II
MRP

ERP II
• Next generation ERP
• System can quickly, accurately and consistently operate
an entire organization
• ERP II solution offers greater flexibility in the integration
of functions between departments and even industries
• ERP II encourages user participation, facilitating
interaction between customers and vendors

Significance of ERP II
1. Industry specific
applications
2. Flexibility
3. Web centric application

Need of ERP system
1. Business Integration
2. Flexibility
3. Better analysis and planning
capabilities
4. Use of latest technology

Characteristic of ERP
1. Accommodating variety – multi facility provided
2. Integrated management information – All in one place
3. Database creation – analysis, reporting becomes easy
4. Seamless integration – integration of new products
5. Supply chain management – flow of demand and supply from end
to end
6. Resource Management - facilitate the effective utilization of
resources
7. Integrated data model – providing data for employees, suppliers
and customers.

Elements of ERP
GUI
Driver
Logic
server
DB
driver RDBMS
Operating System
(UNIX, NT)
Repository

• Advantages:
1. Intangible benefits (qualitative benefits): a,
inventory reduction b, material cost reductions
c, labor cost reductions
2. Tangible (quantitative benefits): a. Effects on
production b. Effects on production and
materials management c. Effects on MIS
function

• Disadvantages:
1. Expense and time in implementation
2. Difficulty implementing change
3. Difficulty integrating with other system
4. Risks in using one vendor
5. Risk of implementation failure

Role of IM in ERP
1. Cycle time
2. Transaction processing
3. Productivity
4. Supply chain management

E-Business
• Electronic business – utilization of formation
and communication technologies in support of
all the activities of business
• E-business includes any process that a
business organization conducts business over
computer mediated network

• Electronic and communication technology
comprised of:
1. E-business
2. E-marketing
3. E-commerce
4. E-operations

Characteristics of E-Business
1. Collaborative product development
2. Procurement and order management
3. Collaborative planning, forecasting and
replenishment
4. Operations and logistics

• E- Business framework consists of
1. Business partners, suppliers, distributers, resellers
2. Employees
3. Supply chain Management
4. Enterprise resource planning
5. Customer relationship management
6. E-procurement

• Advantages:
1. Business survival
2. Finding new customers
3. Retaining existing customers
4. Improvement in process
• Disadvantages:
1. Technical and non – technical limitations
2. Need for hardware and software to evolve

• Applications of E-Business:
1. E - Banking
2. E - trading
3. E - Learning
4. Employment and job market
5. Online publishing
6. E- tailing
7. E- Auctions

E- Governance
• E- Governance is the application of
information and communication technologies
to transfer the efficiency, effectiveness,
transparency and accountability – within
Government and between Government and
etc.,

• E- governance is a form of e-business in
governance comprising of process and
structures involved in deliverance of electronic
services to the public viz., citizens

Objectives of E- governance
1. To build an informed society
2. To increase government and citizen
interaction
3. To encourage citizen participation
4. To bring transparency in governing process
5. To make the government accountable

Model of E-Governance
Community
Management system
Infrastructure
Management System
Knowledge
Management system
Transition
Management system

Advantages of E-Governance
1. Integration of various ministers and departments
2. Documentation, monitoring, and control of various projects
3. Geographic information based system
4. Crime control and management
5. Welfare projects
6. Revenue generation
7. Birth and Death monitoring and control
8. Citizen Identification system

Applications of E-Governance
• Public sector
1. Issue of driving license and registration of
vehicles
2. Payment of taxes, bills and submission of
returns
3. Issue of Passport
4. E- policing

Data Mining
• Data mining – concerned with discovery
knowledge
• Uncovering relationship of patterns
hidden in data that can be used to
predict behaviors, outcomes.

• Knowledge Discovery Databases (KDD)is the non
trivial extraction of implicit, previously unknown
and potentially useful information of data.
• These relationships represent valuable
knowledge about the database and the object in
the database

Components of data mining
1. Database
2. Data warehouse
3. Information
repository
4. Data warehouse
server
5. Knowledge base
6. Data mining Engine
7. Pattern Evaluation
module
8. Graphical user
interface

Data mining Techniques
1. Cluster analysis – unsupervised learning environment
2. Induction – technique to infer information that is
generalized from the database a, decision tress b, rule
induction.
3. Neural networks – remarkable ability to derive meaning
from complicated or imprecise data and can be used to
extract patterns and detect trends
Contd…

4. OLAP – online analytical processing –
relationships among data as a
multidimensional structure
5. Data Visualization – make it possible analyst
to gain a deeper, more institutive
understanding

CRISP – DM (Cross industry standard
process for data mining
Phase 1 • Business understanding
Phase 2 • Data Understanding
Phase 3 • Data Preparation
Phase 4 • Modeling
Phase 5 • Evaluation
Phase 6 • Deployment

Advantages of data mining
1. Automated prediction of trends and
behavior
2. Automated discovery of previously
unknown patterns
3. Databases can be larger in both depth and
breath

Disadvantages of Data Mining
1. Privacy Issues
2. Security Issues
3. Misuse of Information/Inaccurate
Information

Data Mining Applications
1. Retail/marketing
2. Banking
3. Insurance and healthcare
4. Transportation
5. Medicine

Business Intelligence
• The term BI represents the tools and systems
that a key role in the strategic planning
process
• BI systems gather data from multiple sources
and use the analytics and reporting – support
decision making

Key performance Indicators
• Are quantifiable measurements
1. General: year to year measurements
2. Finance: EPS, profit margin and alike
3. HR: applicants to job opening, employee
turnover ratio and alike
4. Education: graduation rates, no. of incoming,
student retention rates

Components of BI (Business
Intelligence)
1. Data extraction, transformation and
loading tools
2. Data store
3. Data query and analysis tools
4. Data presentation and visualization
tools

Advantages of BI
1. Authorize employees
2. Unite people to access data competently and
successfully
3. Simplify team work and allocation
4. Convey BI to the entire firm
5. Examine and increase insight
6. Enhance association
7. Lesson training requirements
8. Transport refined investigation and reporting

Disadvantages of BI
1. Piling of historical data
2. Cost
3. Complexity
4. Disordering of commercial settings
5. Limited use
6. Time consuming implementation

Applications of Business intelligence
1. Measurement
2. Analytics
3. Reporting/Enterprise reporting
4. Collaboration/collaboration platform
5. Knowledge Management

Pervasive computing
• Pervasive means “Existing everywhere” –
ubiquitous computing
• Rapidly developing area of information and
computing technology (ICT)
• May lead to a greater degree of user
technology – control over things (computers)
• Opposite to “Virtual Reality”

Pervasive computing principles
1. Decentralization
2. Diversification
3. Connectivity
4. Simplicity

Pervasive computing techniques
1. Computing devices – 1. sensors 2.
processors 3. Actuators
2. Communications (connectivity)
3. User interface (Human Computer
interaction) – active and passive and
coercive

Applications of pervasive computing
• Could have a range of applications
1. Smart home – highlighting, energy management,
water control, home security and communications,
home theatre
2. Smart appliances
3. Smart cars
4. Smart “things’ – Barcodes and Auto - ID

Cloud computing
• Cloud computing is a type of computing that
rules on sharing computing resources rather
than local servers or personal device to handle
applications
• Word cloud is the ‘metaphor’ for Internet
• The idea of cloud computing is based on a very
fundamental and basic principal of ‘re-usability
of It capabilities”

Characteristics of cloud computing
1. On demand self service
2. Broad network access
3. Resource pooling
4. Rapid elasticity
5. Measured service

Cloud Computing
1. Clients (mobile, thin, thick)
2. Data centre
3. Distributed server

Cloud Computing models
1. Software as a service (SaaS)
2. Platform as a service (PaaS)
3. Infrastructure as a service (IaaS)

Types of cloud computing
1. Public cloud
2. Private cloud – on premise
private cloud and externally
hosted private cloud
3. Hybrid cloud

Capability Maturity model (CMM)
• Capability Maturity model (CMM) – service mark
registered with the U.S patent and trademark office
• - Was originally developed as a tool for objectively
assessing the ability of Government contractors’
processes to perform a contracted software project
• CMM provides the means to measure an organizations
process maturity against a set of common feature that
are specified at each of the maturity lends

KPA (Key Process Area)
• 5 common features
1. Commitment to perform
2. Ability to perform
3. Activities performed
4. Measurement and analysis
5. Verifying implementing

Structure of CMM
Maturity levels
Key process Areas
Common features
Key practices
Process
Capability
Goals
Implementation
Activities
contain
indicate
achieve
Organized by
Address
contain
describe

Levels of CMM (Capability Maturity
Model)
Level 1: Initial level
Level 2: Repeatable level
1. Requirements management
2. Software project planning
3. Software project tracking and oversight
4. Software sub contract Management
5. Software quality assurance
6. Software configuration Management
Contd…

• Level 3: Defined level
1. Organization process focus
2. Organization process definition
3. Training program
4. Integrated software management
5. Software product engineering
6. Inter group co-ordination
7. Peer reviews

• Level 4: Managed level
1. Quantitative process management
2. Software quality management
• Level 5: Optimized level
1. Defect prevention
2. Technology change management
3. Process change Management

Information Management Unit 5 New IT initiatives

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