1. Module 2 Topics
Information technology governance: Organization and planning for IS

2. Management Information Systems
Chapter 5 IT Infrastructure and Emerging Technologies
Management Issues
Dealing with infrastructure change
Management and governance
Making wise infrastructure investments
Competitive forces model for IT infrastructure
Total cost of ownership of technology assets

3. Management Information Systems
Chapter 5 IT Infrastructure and Emerging Technologies
Management Issues
Competitive Forces Model for IT Infrastructure
There are six factors you can use to answer the question, “How much should our firm spend on IT infrastructure?”
Figure 5-15

4. Management Information Systems
Chapter 10 Information Resource Management and Project Management
Selecting Projects
Management structure for information systems projects
Linking systems projects to the business plan
Enterprise analysis and critical success factors
Portfolio analysis
Scoring models

5. Management Information Systems
Chapter 10 Information Resource Management and Project Management
Selecting Projects
Management Control of Systems Projects
Each level of management in the hierarchy is responsible for specific aspects of systems projects, and this structure helps give priority to the most important systems projects for the organization.
Figure 10-4

6. Information Systems Plan
Linking Information Systems to the Business Plan
Information Systems Plan
Road map indicating direction of systems development
The rationale, the current situation, the management strategy, the implementation plan, and the budget

7. Management Information Systems
Chapter 10 Information Resource Management and Project Management
Selecting Projects
Figure 10-6

8. Management Information Systems
Chapter 10 Information Resource Management and Project Management
Selecting Projects
A System Portfolio
Companies should examine their portfolio of projects in terms of potential benefits and likely risks. Certain kinds of projects should be avoided altogether and others developed rapidly. There is no ideal mix. Companies in different industries have different profiles.
Figure 10-7

9. Scoring Models Management Information Systems
Chapter 10 Information Resource Management and Project Management
Selecting Projects
Scoring Models
A quick and sometimes compelling method for arriving at a decision on alternative systems
The most important outcome of a scoring model is not the score but agreement on the criteria used to judge a system
Best practice is to cycle through the scoring model several times, changing the criteria and weights, to see how sensitive the outcome is to reasonable changes in criteria

10. Management Information Systems
Chapter 10 Information Resource Management and Project Management
Selecting Projects

11. Management Issues Capacity planning & scalability
Total cost of ownership (TCO)
Hard to calculate (hardware, software, installation, support, maintenance, training, network connections/ infrastructure, upgrading, life of asset)
Need for comprehensive asset management plan
Software tools to help
Need for long-range strategic planning to deal with these issues

12. Information Resource Management
Stop Here

13. IS Costs formal learning informal learning peer support
applications development
data management
supplies (diskettes, toner, and so on)
end-user downtime
disaster recovery
"futz factor" (time spent surfing the net, playing games,and doing non-work activities)

14. Cost for a business to own a computer

15. Questions for Today
How can we justify investing in IT and systems when everything changes so quickly?
How can we ensure that we get the most out of our systems?
How do we get everyone “on board” an IS development project?

16. Problems in Determining Business Value
Intangible nature of data & systems
Intangible nature of many benefits & costs
Hard to estimate even tangible benefits & costs
Complexity
Risk

17. Traditional Ways to Determine Business Value: Capital Budgeting Models
Payback
Return on investment (ROI)
Cost/benefit ratio
Net present value (NPV)
Profitability
Internal rate of return (IRR)

18. Hierarchy of Data Bit Byte
Field/attribute (key field) (AKA data element)
Record/entity/tuple
File
Database
Database management system

19. File Organization Terms and Concepts

20. Attribute: Description of a particular entity
File Organization Terms and Concepts
Entity: Person, place, thing, event about which information is maintained
Attribute: Description of a particular entity
Key Field: Identifier field used to retrieve, update, sort a record

21. File Organization Terms and Concepts

22. Traditional Data Environment
Files for each application/department/function
Duplicated/redundant data/files
Inability to link data/files
Program-data dependence (change one, you must change the other)

23. Problems with the Traditional File Environment

24. Problems with Traditional Data Environment
Data redundancy leads to
Lack of data integrity
Program-data dependence
Lack of flexibility (no ad hoc reports/different views
Poor security (access)
Lack of data sharing & availability

25. DBMS Approach
Database: Collection of one or more files containing data organized to serve multiple applications by minimizing redundant data.
Database management system controls organization of & access to data and database files by acting as interface between the data & application programs and as an environment for developing and using databases.

26. 7.2 THE DATABASE APPROACH TO DATA MANAGEMENT

27. Views/Schemas
Logical view: How end users perceive the data is organized
Schema: The view of all the data
Subschema: A partial view of the data accessible to an end user (e.g., “view only” a subset of screens/data)
Physical view: How the data are actually organized on physical storage media

28. Components of a DBMS Data definition language (DDL) Data dictionary
Formal language associated with DBMS
Used by both end users & programmers to manipulate data
Data dictionary
Defines each data element (# bytes, text/numeric, etc., format, range, access, use, ownership, physical representation)
Used for communication between developers & users and for standardization of data/databases/ programs
Some data dictionaries are active; changes automatically change related databases/programs

29. Components of a DBMS Data manipulation language
Commands to modify/extract data & to develop apps
Structured Query Language (SQL)
Can use various languages in addition to/ instead of SQL

30. Data/Information Mgmt Issues
Data Integrity
Data Security
Customer Privacy