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Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes loads of requests to computerise crude methods of development and analysis business applications not well understood discouragement and scepticism as a result maturation was required on both theoretical and practical sides (ie: technology and management) IS is established as a discipline (?) and functional area
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Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Dec 21, 2015

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Page 1: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Quick history of IS

• Very rapid growth as a profession and an academic discipline

• early days of “computer is beautiful” lead to mistakes– loads of requests to computerise

– crude methods of development and analysis

– business applications not well understood

• discouragement and scepticism as a result

• maturation was required on both theoretical and practical sides (ie: technology and management)

• IS is established as a discipline (?) and functional area

Page 2: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Has Lead to...• ability to use information systems technology is

essential for success

• some companies apply IT with great benefit; others make no progress at all

• “reactive approach” to IT no longer works– too much novelty too fast

– technology more and more powerful and less and less predictable

• role of business managers in introducing IT has become paramount

Page 3: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Growth of IS

• Number of people involved:– In companies

– In society at large

• Importance:– very visible information systems

– size of investments

• Notoriety:– Internet…

– public perception

Page 4: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Change of Focus in IS:• Very Technical

– specialists’ domain– centralised concentrated expertise– expensive– well guarded– computer based

• Very Managerial– every manager’s business– decentralised awareness– very cheap– service department more open to the outside– information based

Page 5: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

(An) information system is an organised method of providing past, present and projection information relating to internal operations and external intelligence. It supports planning, control, and operational functions of the organisation by furnishing uniform information in the proper time-frame to assist the decision maker.

(Kenneron, 1970)

Early definition of IS

Page 6: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

(An information systems is a) system which assembles, stores, processes and delivers information relevant to an organisation (or to society), in such a way that the information is accessible and useful to those who wish to use it, including managers, staff, clients and citizens. An information system is a human activity (social) system which may or may not involve the use of computer systems.

(Avison & Fitzgerald, 1988)

Another definition centred on Human Activities?

Page 7: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

One of the components (or sub-systems) of an organisation is the information system. The components of this system are people, hardware, software, data and procedures.

(Ahituv & Neumann, 1990)

Another definition centred on the social integration of IS

Page 8: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

An information system is a formalised computer information system that can collect, store, process, and report data from various sources to provide the information necessary for managerial decision making.

(Hicks, 1993)

Another definition centred on Computer Systems

Page 9: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

• General definition (Oxford):

“News, intelligence or knowledge communicated; the act of informing”.

• In management terms:

“Data which have been processed by a human mind”

What is Information?

Page 10: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

• The result of a process whereby:

What is Information?

DATA

Human Mind

INFORMATION

Page 11: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Information System

DATA

Computer

INFORMATIONINFORMATION

Page 12: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Starting Point:

1 - Information is a key corporate resource

2 - Information must be regarded as an investment

3 - Information systems are a strategic resource that can generate competitive advantage and Competitive advantage is what makes companies win

Page 13: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Information as a key resource:

• General examples:– Travel agent

– Stock traders

• Within a company:– Profit

– Status of customer orders

– Productivity

– Stock levels

– Market share

– Opinions of customers

Page 14: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Information as Investment:

• Information is not freely available

• Information has a cost– eg?

• Information has benefits:– eg?

• Decisions to invest in Information

Page 15: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Information for competitive advantage:

Mickael Porter and Victor Millar (1982)

• information technology is changing the way companies operate internally and externally

– it alters industry structures

– it supports differentiation strategies

– it opens new businesses

• New technologies can be used to exploit information to gain competitive advantage

Page 16: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Analysis of existing SIS:

• SIS were never intended to be strategic

• They rarely involve radically new technology

• They rarely originate in the IT function

• They are generally based on a “first mover” advantage, but there have been some striking counter-examples

• Ability to handle huge amounts of information is often main factor - ie: use of DBs

Page 17: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Evidence of the Importance of IS

• Change in the nature of applications

• Change in the perception of top managers– 3 eras (Read Rockart

• Development of Strategic Systems– change the nature of the relationship with customers /

competitors / suppliers

– provide better integration of information usage

– enable organisations to deliver new services or products based on information

– provide information to managers for strategic purposes

Page 18: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

• American Hospital Supply Corporation (AHSC): system whereby customers can directly re-order their supplies from terminals located in their hospitals

• Successful because it enabled AHSC’s customers to cut their costs of administration

• originally meant as an INTERNAL systems by AHSC and extended to one main customer

Link with suppliers:

Page 19: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Improved Integration of Internal processes

• SABRE (American Airlines): first effective electronic reservation systems in the US

• simple one-line database application

• took a long time to justify the investment

• competitive value of system still felt today

• in 1988 AA were making more money out of SABRE than out of flying air planes

Page 20: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Information Based products

• Merrill Lynch’s integrated banking service

• cash management account

• combined up to then separated services into a single statement

• automatically moved funds to higher interest accounts

• Merrill Lynch captured assets worth $1 billion in the first year alone

Page 21: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Provision of Executive Information

• EIS

• Greater visibility on the work of lower levels enables greater levels of delegation

• Acceleration of communication

• Support for collective decision making

• Access to external information

• etc...

Page 22: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Formal Techniques to exploit IT

• Business System Planning (BSP): IBM in the 1970s– 13 different steps– very cumbersome, expensive and long

• Strategic Planning for IT– to provide a solid technical foundation– alignment with the corporate strategy

• Application Generator: C. Wisemann– aimed at outside opportunities– up to 100 potential applications per company

Page 23: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

More Formal Strategic Models - BSP

• Business Systems Planning (BSP)

• Proprietary IBM technique mid 70s

• Data flow mapping technique - output of one process becomes input into another

• Geared towards the creation of a central data repository

• top-down planning followed by bottom-up implementation

• Huge costs huge volumes of documentation

• Little possibility to build-in the competitive position of the firm

Page 24: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Porter’s Competitive Analysis (1980)

• based on the “five forces” matrix

• scope includes the entire business

• According to the framework, organisations' ability to compete is determined by:

The threat of new competitors

The threat of substitute products or services

The bargaining power of customers

The bargaining power of suppliers

The rivalry amongst existing competitors

Page 25: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Rockart’s CSF method:• Identification of a hierarchy of performance measures

that lead to identification of Critical Factors and Issues that will determine a business’ success

The business mission statement

The business vision statement

multiple business goals

multiple business objectives for each goal

multiple CSFs for each objective

See Figure 2

Page 26: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

McFarlan and McKenney’s framework:

High

Low

Strategic Potentialof IS/IT

Strategic Importanceof Current IS/IT

HighLow

Turnaround

Support

Strategic

Factory

Page 27: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

McFarlan and McKenney’s framework:

High

Low

Strategic Potentialof IS/IT

Strategic Importanceof Current IS/IT

HighLow

EducationFarming

Cement FactoryFuneral Homes

NewspaperBanksTravel agents

Retail businessRestaurants

Page 28: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Quick Introduction to Tutorials

• MS Access: Development of Database Applications

• Cheap well-known Relational Database engine

• Includes a complete user-friendly environment for the development of applications:– Interface,

– report generator,

– menus and forms

– multiple wizards

• Also a bit of Oracle: to learn how to use structured query language (SQL).

Page 29: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Basics of data Organisation:

DATA HIERARCHY (four categories)

• Fields = represent a single data item

• Records = made up of a related set of fields describing one instance of an entity

• File = a set of related records - as many as instances in the set

• Database = a collection of related files

Page 30: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Example of data structure

Name First name Telephone

Borg Bjorn 45 25 65 65Healy Margaret 25 58 96 63McEnroe John 12 25 28 89Cantona Eric 25 78 85 85

Fields

Records

File + Other filesie: more information

Page 31: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

"A collection of interrelated data stored together with controlled redundancy, to serve one or more applications in an optimal fashion; the data is stored so that it is independent of the application programs which use it; a common and controlled approach is used in adding new data and in modifying existing data within the database."

Database: Definition.

Page 32: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

• A collection of interrelated data stored together

• with controlled redundancy

• to serve one or more applications in an optimal fashion

• the data is stored so that it is independent of the application programs which use it

• a common and controlled approach is used in adding new data and in modifying existing data within the database.

Definition - closer look

Page 33: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Advantages of Databases:

• data are independent from applications - stored centrally

• data are accessible to any new program

• data are not duplicated in different locations

• programmers do not have to write extensive descriptions of the files

• These save enough money and time to offset the extra costs of setting and maintaining DBs

Page 34: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Disadvantages of DBs:

• Data are more accessible so more easily abused

• DBs require expensive hardware and software

• specialised personnel is often required to start with large DBs (but not Access!!)

• people may object to “their” data being widely available in a DB (information is power??)

Page 35: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

DataBase Management System (DBMS):

• program that makes it possible to:– create

– use

– maintain

a database

• provides a logical access to the data stored in the DB

• users/programmers do not have to worry about the physical aspects of the DB

Page 36: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Using a database:Two main functions of the DBMS :

• Query language - for people who are not programmer (greatest advantage of DB)

• Data manipulation language - for programmers who want to modify the links between data elements within the DB

• Also, Host Language - the language used by programmers to develop the rest of the application - eg: Cobol, Fortran, Visual Basic......

Page 37: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Different types of DBs:

• creating the DB = specifying the links between data items

• different types of relationships can be specified - ie different logical views

• they correspond to three main types of DBMSs:– Hierarchical DBs

– Network DBs

– Relational DBs (most frequent)

Page 38: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Relational DBs:• Data items stored in tables (records + fields)

• Specific fields from each table related to other fields in other tables (joint)

• infinite number of possible viewpoints on the data (queries)

• most flexible of all DBs but slower for complex searches (many connections to follow)

• Oracle, SyBase on Unix, Access, Paradox for Windows...

Page 39: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Describing relationships

• Attempt at modelling the business elements (entities) and their relationships (links)

• Can be based on users’ descriptions of the business processes

• Specifies dependencies between the data items

• Coded in an Entity-Relationship Diagram (ERD)

Page 40: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Types of Relationships

• one-to-one: one instance of one data item corresponds to one instance of another

• one-to-many: one instance to many instances

• many-to-many: many instance correspond to many instances

• Also some relationships may be:– compulsory– optional

Page 41: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Example

• Simple Sales Ordering

• What are the entities?

• What type of relationship do they have?

• Draw the diagram

Page 42: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Entity Relationship Diagram

Page 43: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Next step - creating the data structure

• Few rules - a lot of experience

• Can get quite complex (paramount for the speed of the DB)

• Tables must be normalised - ie redundancy is limited to the strict minimum by an algorithm

• In practice, normalisation is not always the best

Page 44: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Data Structure Diagrams

• Describe the underlying structure of the DB: the complete logical structure

• Data items are stored in tables linked by pointers– attribute pointers: data fields in one table that will link it to another

(common information)

– logical pointers: specific links that exist between tables

• Tables have a key just like files

Page 45: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

ORDER

order numberItem descriptionItem PriceQuantity orderedCustomer numberItem number

Item

Item numberItem descriptionItem costQuantity on hand

Customer

Customer numberCustomer nameCustomer addressCustomer balanceCustomer special rate

1

2

3

4

* compulsory attributes0 optional attributes

Page 46: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Normalisation

• Process of simplifying the relationships amongst data items as much as possible (see example provided - handout)

• Through an iterative process, structure of data is refined to 1NF, 2NF, 3NF etc.

• Reasons for normalisation:– to simplify retrieval (speed of response)– to simplify maintenance (updates, deletion, insertions)– to reduce the need to restructure the data for each new application

Page 47: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

First Normal Form

• design record structure so that each record looks the same (same length, no repeating groups)

• repetition within a record means one relation was missed = create new relation

• elements of repeating groups are stored as a separate entity, in a separate table

• normalised records have a fixed length and expanded primary key

Page 48: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Second Normal Form

• Record must be in first normal form first

• each item in the record must be fully dependent on the key for identification

• Functional dependency means a data item’s value is uniquely associated with another’s

• only on-to-one relationship between elements in the same file

• otherwise split into more tables

Page 49: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Third normal form

• to remove transitive dependencies

• when one item is dependent on an item which is dependent from the key in the file

• relationship is split to avoid data being lost inadvertently

• this will give greater flexibility for the design of the application + eliminate deletion problems

• in practice, 3 NF not used all the time - speed of retrieval can be affected

Page 50: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Creating links between the tables

• use common fields to join tables / queries

• very easy when data is properly normalised

• Gives total flexibility in terms of data retrieval

• Main strength of RDBs (SQL)

Page 51: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Structured Query Language

• used for defining and manipulating data in Relational DBs

• aimed at:– reducing training costs– increasing productivity– improve application portability– increase application longevity– reduce dependency on single vendors– enable cross systems communication

• In practice, SQLs can be a bit different

Page 52: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Querying RDBs with SQL• use a form of pseudo english to retrieve data in a view (which looks

like a table)

• syntax is based on a number of “clauses”

• Select: specifies what data elements will be included in the view

• From: lists the tables involved

• Where: specifies conditions to filter the data– specific values sought

– links between tables

Page 53: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Example with one table

• find the name and address of customer number 1217

Select name, address

from [customer table]

where cust. # = 1217

Page 54: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Example with a range

• find the items which are priced between £50 and £15000

Select item#, description, price

from [item table]

where price > 12000 and price < 20000

Page 55: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Example with two tables

• find the rep name of all customers

select [customer table].name, [rep table].[rep name]

from [customer table], [rep table]

where [customer table].[rep#] = [rep table].[rep #]

Page 56: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Example with two tables

• same for customer Murphy only

select [customer table].name, [rep table].[rep name]

from [customer table], [rep table]

where [customer table].[rep#] = [rep table].[rep #]

and [customer table].name = “murphy”

Page 57: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Use of a Search Condition - nested queries

• find the name and address of the customer who ordered order # 110

select name, address

from customer table

where cust. # =(select cust. #

from order table

where order# = 110)

Page 58: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Additional syntax

• Add computation in the “select” statement:– select SUM(price)

– select AVG(price), MAX, MIN, COUNT

• Simplify comparisons with a BETWEEN clause and LIKE clause (with *, ?)

• Add sorting instruction after the where clause– ORDER BY name (alphabetical)

– ORDER BY price (ascending)

• Provide aggregate information by grouping data:– GROUP BY customer

Page 59: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

• find contents (item# and description) of order 110:

Select [item table].item#, [item table].descriptionFrom [item table], [order line table]Where [item table].item# = [order line table].item#

and [order line table].order# = 110

Page 60: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

• find the average price of the cars for sale

• find the average price of all orders taken so far by customer “Adam”

Select avg(price)From [item table]

Select [item table].avg(price)From [item table], [order line table], [customer table],

[order table]Where [item table].item# = [order line table].item#

and [order line table].order# = [order table].order#and [order table].cust# = [customer table].cust#and [customer table].name = “Adam”

Page 61: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

• find how much cash customer “Bowe” has generated in total

Select SUM([order table].total)From [order table], [customer table]Where [order table].cust# = [customer table].cust#

and [customer table].name = “Bowe”

Page 62: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

find the average price of all orders taken so far

Select AVG(total)From [order table]

Page 63: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

First Sessions:

• Check out what the Access environment looks like

• Understand how the building blocks available fit together:– tables

– queries

– forms

– reports

– macros

– modules

• Learn how to use some of the wizards

Page 64: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.
Page 65: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

CUSTOMER TABLE

PRODUCT TABLE

ITEM TABLE

SALES_ORDER TABLE

PRICE TABLE

Oracle Demo Set -Sales Order Processing

Page 66: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

DEPARTMENT TABLE

EMPLOYEE TABLE

JOB TABLE

LOCATION TABLE

Oracle Demo Set -Employee Data

Page 67: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Functions of Database Management Systems

• Data storage retrieval and update facilities

• A user-accessible catalogue or data dictionary

• Support for shared update

• Backup and recovery services

• Security services

• Integrity services

• Services to promote data independence

• Telecommunications

• Utilities

Page 68: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Support for Logical Transactions

• logical transaction = many separate physical transactions (reading, updating, writing records)

• if transaction are interrupted before entire completion "up to date" data is sacrificed for consistent data.

• If not, transaction is committed - ie written to disk

• DBMS provides mechanisms that either Commit or Rollback transactions

Page 69: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

SHARED UPDATE• i.e. Two or more users making updates to database at the

same time– Single vs. Multiuser Environment (eg: Networked DBMS)

• Problem: double update– CUSTOMER BALANCE: 418

– Pat (recording sale: +100) and Jo (recording payment -100):

– CORRECT: Pat reads, updates and writes (commits: 518). Jo reads (518), updates and writes (commits: 418).

– VALUE: 418.

– INCORRECT: Pat reads and updates. Jo reads and updates. Pat writes (commit: 518). Jo writes (commit: 318).

– VALUE: 318.

Page 70: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

SHARED UPDATE - SOLUTIONS

• 1. AVOIDANCE:– Prohibit shared update,

– Allow access for retrieval only,

– Record updates in transaction file and update database periodically using a batch program.

• Problem: Data is temporarily out of date

• customer may not be allowed credit because his balance had not been credited with last payment.

Page 71: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

• 2. LOCKING– Lock table/record/field from access by other users.

• TYPES OF LOCK– Exclusive Lock

– Read Only Lock

– Lock Time-Out

• Other variables– Lock Granularity

– Deadlock

SHARED UPDATE - SOLUTIONS

Page 72: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

• TYPES OF LOCK– Exclusive Lock: Other users can neither read nor update locked

table/record/row. Extreme and inflexible.– Read Only Lock: Other users can read but not update the locked

table/record. – Lock Time-Out: If a record is locked, a user could have a long wait

for its release. Some DBMS's detect lengthy locks and unlock them, undoing any updates made to any records during the transaction.

– Lock Granularity: Refers to the level of the lock: field, record, page/block, table.

– Deadlock: Users can have a lock on more than one record at a time. This poses problems when two users require each others locked records.

Page 73: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

RECOVERY

1. Backups or Saves (normal backup of DB files)

2. Journaling / Audit trail / Audit file– Keep a log or journal of the activity which updates the database

– recovery involves: Copying the backup over database and running a special program to update the backup version of the database with the transaction in the log.

Page 74: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

SECURITY• Restriction of access to authorised users only.

1. Passwords

2. Encryption

3. Views

4. Authorisation Levels• read only

• edit

• delete

• create

Page 75: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Data Integrity

• DBMS provides a mechanism to enforce specific rules. – Examples:

*Customer numbers must be numeric,

• But programmers must also develop their own

* Credit Limits must be £300, £500 or £1000 only,

* The sales rep for a given customer must exist,

* No customer may be deleted if he/she currently has an order on file.

Page 76: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Data Independence

• DBMS must support the isolation of data structure from the programs

• Users or application programs not be affected by changes to the database structure. (no reprogramming or recompilation)

• Logical and Physical Data Independence Usually achieved through Subschema or View type mechanisms.

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Database Schema

• description of the overall logical structure of a database, expressed / programmed in Data Definition Language (DDL)

• broken down into sub-schemas: logical description of a user’s view or program’s view of the data used

• DDL can be very sophisticated on a mainframe or trivial on a PC (queries / views)

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Telecommunication

• organisations are rarely single site / single entity

• flows of data transcend the boundaries of organisations - so do information systems

• data communication must be implemented

• databases can be used to support the distribution of information resources

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Integration of applications

• organisational data sources are varied

• all applications must be integrated to save time (ie: exchange data)

• databases can be used to enable this integration (eg: MFG/PRO)

• portability / compatibility is paramount (eg: ODBC drivers)

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Database Utilities

• Compact datafiles

• Index / re-index data files

• Repair database (crash)

• Import/export data from and to other sources

• Enforce standards (eg: integrity of relationships, NF...)

• Associated data dictionary

• Access to remote computers (login, emulation)

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Distributed Databases• Logical next step in geographically dispersed

organisations

• goal is to provide location transparency

• starting point = a set of decentralised DBs located in different places, developed for the specific information needs of each site

• Aim: to integrate these decentralised DBs into a coherent DDB

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Advantages of Distributed DBs:

• Increased reliability of systems and availability of data

• Local control preserved

• Modular growth possible at each site and at new sites

• Optimised communication costs

• Faster response times

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Control in normal DBs

• transaction control: ability of the DBMS to ensure the successful completion of transactions– commit transactions

– roll-back to previous state

• concurrency control: ability of the DBMS to arbitrate between concurrent uses of data:– simultaneous access

– simultaneous update

– deletion

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Control in Distributed DBs

• Different portions of the overall database reside at different locations

• these portions are controlled by different processors running sometimes different DBMSs

• common schema means queries can involve any portion of the DB residing at any location

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Options for Distributed DBs

• Issue of physical design (data structure)

• performance of the DB (response time...) depends upon good design

• There are a number of options:– data replication

– horizontal partitioning

– vertical partitioning

– combinations of the above

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Data replication

• store a separate copy of the full tables in each location

• if a copy is stored at every site: Full Replication

• Advantages:– reliability

– fast response

• Disadvantages– storage requirements

– complexity and cost of updating

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Horizontal partitioning

• some of the rows of the tables are stored in one location; others are stored at other locations

• eg: customers banking out of a particular branch

• Advantages:– efficiency– local optimisation– security

• Disadvantages:– inconsistent speed access– backup vulnerability

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Vertical partitioning• some columns are projected into base relationship at different sites

• all relations share a common domain so the full table can be reconstructed

• Advantages:– tailor-made support for functional areas

– same as horizontal partitioning

• Disadvantages:– some queries might be very slow

– users must understand some design issues

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Combinations of the three methods

• most of the time, companies will use different methods

• each method is efficient in certain situations + some other security requirements

• eg: local customers, information originating at a certain site, shared processes that require the same data at all sites

• it is a design issue to try to identify the optimal distribution - data at the sites where it is used most

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Distributed DBMS

• additional roles to play in the case of a distributed DB

• determine the location where data to be retrieved is located

• translate the request into the language used by the local DBMS

• deal with normal data management functions, security matters, locking, query optimisation...

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Heterogeneous Distributed DBMS

• a different DBMS running at each site

• a master DBMS controlling the interactions amongst the parts

• not practical today (compatibility)

• more often, each DBMS follows the same data architecture

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Problems with global transactions

• DBMSs can be radically different - relational versus network

• only some state-of-the-art commercial products have translating capabilities

• one alternative solution is to put some essential data and the directory of the data locations on a central server

• Real distributed DBMS solve these problems for the users with the help of the NOS

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Commit Protocol• to ensure the integrity of the data in update operations

• well defined procedure based on the exchange of messages (“ok” or “not ok”)

• each global transaction can either be complete (and completed) or aborted

• Two-phase commit:– site originating the transaction sends requests to all sites involved in the update

– all sites attempt to process their part of the transaction without committing the data (temp files)

– they notify the first site whether OK or not

– the first site collects all OKs and sends order to commit the data

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Timestamping

• Alternative to locking (possibility of deadlocks)

• ensures that transactions are processed in serial order so locking in not needed

• All updated records carry the timestamp of the transactions that modified them

• if new transaction attempts to update a record with an earlier timestamp = OK

• If new transaction ...with a later stamp, update access is denied, the transaction is re-stamped and is re-started

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Updated record

Updated record

Example:

168

Record update: 170 OK

170

Record Update: 165 Denied

Record Update: 170 Transaction re-started (ie: do it again)

170

Record in a DB

+++: costly deadlock situations are avoided----: transactions may sometimes be restarted even thoughthey did not conflict with previous ones.

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Effect of design on speed• how to design fast queries

• simple example with two sites in relational DB:– supplier (Supplier#, ...,City): 10,000 records stored in Detroit– part (part#, .., colour): 100,000 records stored in Chicago– Shipment (supplier#,..., Part#): 1,000,000 records stored in Detroit– each record is 100 characters long + there are 10 red parts– data transmission is 10,000 character/second, 1 second delay in any

communication– data processing negligible

• Write the SQL statement

• Imagine how the query can be carried out between the two sites

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SQL statement

select supplier.supplier#

from supplier, part, shipment

where supplier.city = ‘Cleveland’

and supplier.supplier# = shipment.supplier#

and shipment.part# = part.part#

and part.color = ‘Red’

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Conclusions

• Reasonably easy to optimise query with two tables

• Very complex with more than two (try with 30!)

• Rules:

• Queries must be broken down into components isolated at different sites (minimise communication time and traffic)

• Determine which site has the potential to yield FEWER selected records

• Move preliminary results to site where rest of the work can be performed (ie: try to move as few records as possible)

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Problems with Information Systems:

The following is a quote by the Finance Director of a major UK firm:

“Computer people are painful people, they really are bad. The gap is between my problems and getting them solved, but our people don’t understand that, they are just programmers, they know nothing about management, nothing about financial information and nothing about financial information structures”.

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Scope of IS Development

• Software development is labour intensive

• Large software projects are amongst the most expensive undertakings:

– more than a domed football stadium– more than 50 floor building– more than a 70,000 tons cruise ship

• Managers have unrealistic expectations

• Large software projects have very high failure rates

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Complexity inherent in IS development

• Complexity of IS is not accidental (Brooks)

• Problems tackled are complex

• Project Management is difficult

• Increasing flexibility allowed by tools adds complexity

• Computers need “discretisation” of often continuous situations

• External complexity is added by economic / political constraints on the system

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Failure rates

Fate of IS Projects

Faith of IS projects - Standish Group (1995)

+ effect of size

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Abandoned projects

• Economical and technical factors are not major

• Organisational factors:– loss of management commitment

– political and inter-personal conflicts

• Many well-known examples of failure of large systems in last few years

• Notion of failure is uncertain in IS– eg: Socrate

– different types of systems (as per the Application Portfolio Analysis Matrix)

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Systems Development Life Cycle:

• SDLC is a Disciplined approach to systems development

• it cannot guaranty the success of the developments, but provides a number of useful rules and guidelines

• There are many version of SDLC (nearly as many as authors) but they nearly all say the same thing

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What is an SDLC?• SDLC stands for Systems Development Life Cycle

• it is a methodology (ie - a number of related methods and techniques) aimed at facilitating and making more reliable the development of new information systems

• it consists in breaking down the process in a number of well-defined stages (five) and sub-stages

• those sub-stages can, in turn, be broken down in small tasks which take one person a few days to carry out.

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Principles underlying SDLC:Principle #1: Get the user Involved

• there is a need to attempt to bridge the gap between technical people and users

• the ultimate “owners” of the systems are the users - they must like it

• their opinion and agreement must be sought by the analysts

• Failure to do so will mean the system is useless

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Principle #2: Use a problem solving approach

• ‘Problem’ means opportunity for improvement

1 - Identify the opportunity for change

2 - understand the context surrounding it

3 - define the requirements of a solution

4 - identify a number of such solutions

5 - select the “best” one

6 - design and implement it

7 - monitor acceptance and usage to refine solution

Principles underlying SDLC:

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Principle #3: Establish phases and activities

• SDLCs consist of a number of phases

• the most recent SDLCs have additional phases based on experience of what is needed

• when projects become too large, phases must be broken down into tasks and sub-tasks

• This makes project management easier (you can check if the project is on track more often)

Principles underlying SDLC:

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Principle #4: Establish standards for development and documentation

• projects involve many people each working on a number of sub-tasks

• ultimately all the parts that people developed must be integrated into a coherent system

• This requires consistency in the procedures used and the documentation written

Principles underlying SDLC:

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Principle #5: Justify systems as capital investment

• information systems must be regarded as investments to be maintained

• development choices should be guided by considerations of Cost Effectiveness

• Budgets and schedules are not a rough guidelines, they must be followed and deviations from them must be accounted for

Principles underlying SDLC:

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Principle #6: Cancel and revise the scope of the projects

• after the completion of every sub-task, there is an opportunity to revise the project

• if the project is going nowhere, the decision to abandon it should be contemplated

• the fact that money has been spent on a bad project does not mean it should be finished (even more money will be spent)

Principles underlying SDLC:

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Principle #7: “Divide and Conquer”

• All systems are part of larger systems or networks (eg: WAN) called SuperSystems

• Most systems are made up of smaller systems called SubSystems

• All these need to be taken into account so they neatly fit within one another

• if a system requires changes in the supersystem, the time/cost to do that must be build into the time/cost of development of the new system

Principles underlying SDLC:

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Principle# 8: Design systems for growth and change:

• real shortage of IS staff in organisations means backlog of applications to be developed

• IS analysts should try to develop systems that meet more than just Today’s user needs

• because more time is spent “fixing” old systems than developing new ones

• IS staff need to be more pro active

Principles underlying SDLC:

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A Systems Development Life Cycle:

SystemsPlanning(Planning Analysts)

SystemsSupport

(Systems Analysts

Designers and

Builders

SystemsAnalysis(Systems Analysts)

SystemsDesign

(Designers)

SystemsImplementation

(Systems Builders)

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SystemsPlanning(Planning Analysts)

SystemsSupport

(Systems Analysts

Designers and

Builders

SystemsAnalysis(Systems Analysts)

SystemsDesign

(Designers)

SystemsImplementation

(Systems Builders)

Initiation Stageof a new system:

Owners

Users

Business Mission

B.I.S Plan

PlannedApplications

UnplannedApplications

UnplannedApplications

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SystemsPlanning(Planning Analysts)

SystemsSupport

(Systems Analysts

Designers and

Builders

SystemsAnalysis(Systems Analysts)

SystemsDesign

(Designers)

SystemsImplementation

(Systems Builders)

Analysis Stage of a new system:

Users

Existing system’s details and limitations

Facts andRequirements

AnalysisReport

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SystemsPlanning(Planning Analysts)

SystemsSupport

(Systems Analysts

Designers and

Builders

SystemsAnalysis(Systems Analysts)

SystemsDesign

(Designers)

SystemsImplementation

(Systems Builders)

Design Phase of a new system:

UsersOpinions andRecommendations

Technical DesignReport

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SystemsPlanning(Planning Analysts)

SystemsSupport

(Systems Analysts

Designers and

Builders

SystemsAnalysis(Systems Analysts)

SystemsDesign

(Designers)

SystemsImplementation

(Systems Builders)

Implementation Stage of a new system:

UsersEnd-user trainingand documentation

Actual InformationSystem Delivery

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SystemsPlanning(Planning Analysts)

SystemsSupport

(Systems Analysts

Designers and

Builders

SystemsAnalysis(Systems Analysts)

SystemsImplementation

(Systems Builders)

Support Stage of a new system:

UsersAdditionalTraining and Support

Problems usingthe new systems

Existing system’sLimitations

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Breakdown of SDLC• the five stages of SDLC are PLANNING, ANALYSIS,

DESIGN, IMPLEMENTATION and SUPPORT - commonly broken down into a number of sub-stages as follows:

– system planning:• 1 - study the business mission• 2 - define an information architecture• 3 - evaluate business areas

– system analysis:• 1 - survey project feasibility• 2 - study and analyse current system• 3 - define and prioritise user’s requirements

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– system design:• 1 - select the design target

• 2 - acquire necessary hardware and software

• 3 - design and integrate the new system

– system implementation:• 1 - build and test networks and databases (if any)

• 2 - build and test the programs

• 3 - install and test the new system

• 4 - deliver the new system into operation

– system support:• correct errors

• recover the system (after a crash)

• assist the users of the system

• adapt the system to new / evolving requirements

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Systems planning:

• most organisations do not have planning phases in their SDLC

• priority given to most influential / wealthy departments regardless of potential importance of project for the business

• on-going process to ensure that:– information systems are developed according to the plan– management decisions and external factors have not changed the plan

• made up of three phases

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Systems planning - definition:

• “The systems planning function of the life cycle seeks

to identify and prioritise those technologies and

applications that will return the most value to the

business.”

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Study the Business Mission

• All businesses have a mission (formulated or not)

• only way to ensure that ISs return value to the business is to make them address that mission

• scope of the phase covers the entire business

• Key actor in this phase is the Planning Analyst

• Deliverable is the Business Plan

Systems planning - Phase 1:

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Define an information system architecture:

• design of an IS plan that mirrors and supports the Business plan

• plans must take into account existing systems, opinions and recommendations of users and technology forecasts

• actors involved are the same as in previous phase

• deliverable is the IS plan

Systems planning - Phase 2:

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Evaluate business areas:

• They are groups of logically related functions and activities (concerned with the same processes)

• the overall plan needs to be refined to detail what is needed in the different business areas

• Business Area Analysis (BAA) is very time consuming (several months per area)

• managers and users in specific BAs must be involved as potential developments must be prioritised

• deliverables are individual planned application development projects

Systems planning - Phase 3:

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Systems Analysis:

• It is the study of a current business and information system and the definition of the requirements of the users for a new IS

• it is triggered either by a planned project (previous phase) or by a spontaneous request by a user or owner

• It is made up of three phases

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Survey project Feasibility:

• Feasibility and investment evaluation are crucial (is system worth looking at?)

• short 2 to 3 days preliminary study:– plans

– problems

– opportunities...

• definition of the scope of the project

• systems analysts are main actors but users provide all the information

Systems Analysis - Phase 1:

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• the deliverable is a report recommending:– a quick fix

– or an enhancement of an existing systems

– or a completely new application

• this report is reviewed by the system owners who:– approve the project and push it to next phase

– or change the scope and push it to next phase

– or reject the project

– or postpone the project in favour of another one

Systems Analysis - Phase 1:

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Study and analyse the current systems:

• Analyst must acquire a thorough understanding of:– problems

– opportunities

– constraints and preferences of actors

• He/she delivers a Business Problem Statement submitted to the system owners

• after approval, analysts will produce a system’s objectives report to be passed to the next phase

Systems Analysis - Phase 2:

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Define and Prioritise User’s Requirements:

• Find out exactly “what” the system will offer to the users

• main source of complaints about systems is “system does not do what we want” - ie too much emphasis on the “how”

• Also try to assign priorities to requirements in case some of them are sacrificed by Systems Owners

Systems Analysis - Phase 3:

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• In addition to the common paper-based Analysis Report, two methods can be used for this phase

• “Modelling” or using graphical representations to help user understand what the system might be like

• “Prototyping” or creating a partial version of the system which offers only some of the functions

• faster to develop• cheaper to develop• user can give immediate + reliable opinion on design

Systems Analysis - Phase 3:

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System Design:

• Given the detailed description of the users’ requirements (Analyst’s Report), technical translation of what the system does into how it works

• it consists in the specification of a detailed computer-based solution

• Also called Physical Design

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System Design - Phase 1:

Select a design Target:

• selection of a number of feasible design solutions

• How much of the system should be computerised?

• should we purchase software or develop it ourselves?

• what technology and type of computer would be useful for this system?

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Selection of the “best” design solution:

• Technical feasibility - Do we have expertise?

• Operational feasibility - How will this affect the users’ work (will they resist)?

• Economic feasibility - Is it cost effective?

• Schedule feasibility - Can it be done within acceptable timeframe?

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Result of the first phase:

• a solution is selected - often a combination of the best options

• finally, a Systems Proposal is put forward to the Systems Owners

• Systems Owners might:– Approve and fund the solution

– Select and fund one of the design solutions

– Reject the solutions and cancel the whole project or send it back for more

– Approve a reduced-scope version of the solution

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Systems Design - Phase 2: Acquire necessary Hardware and Software:

• more and more software are purchased off-the-shelf by organisations

• Selection process is crucial and not well understood yet

• shop around for the lowest price

• shop around for the best service - potential danger area

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+ / - of buying “turn-key” solutions:

• system very reliable

• system can be seen in operation before buying (users may even be interviewed)

• project much easier to schedule

• no need to have all expertise involved in-house

• Less risk that project is going to cost more than expected

• some degree of customisation is often possible

• maintenance / support is part of the contract

++

++

+

+

+

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• no guaranty that required system exists

• selection of a supplier is difficult and time consuming

• difficult to say when one has contemplated enough solutions

• potential expertise gap when buying

• difficult to get any competitive advantage out of a system that everyone can buy

• situation becomes unmanageable in multi-supplier situations

+ / - of buying “turn-key” solutions:

--

-

-

--

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Design - phase 3:Design and integrate the new system

• given the approved, feasible solution, system can finally be designed - ie planning how it will work

• in addition, designers ensure that it will work in harmony with existing systems

• the general design involves the structure of files and DBs, the processing methods, the structure of networks...

• the detailed design involves the internal design (program logic) and external design (user interface)

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Systems Implementation phase:• this is the construction of the new system (or its

development)

• it is totally based on the results - ie the reports of the design phase (often called Technical Design Statement)

• it is made up of four phases:– build and test networks and DBs (optional)

– build and test the programs (documentation, testing)

– install and test the new system

– deliver the system (user documentation, training)

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System Support phase:

• it involves the on-going maintenance of the system after its delivery

• it also includes improvements to the system

• it is made up of a number of on-going activities rather than sequential phases:

– correct errors (bugs, lack of robustness...)

– recover the system (crash, processing error...)

– assist the users of the system

– adapt the system to new requirements

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Adapt the system to new requirements

• new business problems identified by the users

• ideas for enhancement as identified by users or analysts

• new technical problems brought by evolving circumstances (year 2000, increase in volume...)

• new technology available on the market which can simplify or improve existing application

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Cross Life Cycle Activities:• activities that cover more than one phase

• activities that recur in a number of phases

– fact finding (also data collection or information gathering)

– documentation - recording facts and specification of the system

– presentation - formally packaging the documentation

– estimation - approximating time, effort, costs and benefits

– measurement - measuring and analysing productivity and quality

– feasibility analysis

– project management - overall co-ordination and supervision activity for the whole project

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Techniques and Methods in use during SDLC phases:

• tools and techniques for the initial steps– fact finding techniques used to collect information

– tools and techniques to organise the data collected and identify the gaps

• techniques for systems analysis - structured analysis– graphic symbols - data flow analysis

– data dictionary

– techniques to document procedures and decisions

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Fact finding techniques:

Interviews: structured or unstructured and with individuals or with groups

• often favourite methods of analysts but not necessarily best method

– time consuming

– can turn into questioning

– not suitable for quantitative information

– personal bias can occur (how to verify information???)

– personality clashes can occur

– requires a lot of skill from analyst

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Interviews (2)

• however, it can be very useful:– for people who are not good at communicating in writing

– for people who do not have time to reply to questionnaires

– to discover areas of mis-understanding

– to identify potential resistance to change

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Questionnaires:

• ideal to collect data from very large number of users

• standardised questions mean more reliable information

• anonymous answers are possible

• can use open-ended or close-ended questions

• However, problems can arise as:– people can misunderstand questions

– it is difficult to evaluate how competent people really are

– it is difficult and time consuming to design good questionnaires

Fact finding techniques:

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Record review:

• records include written policy manuals, standardised operating procedures, guides...

• unfortunately, they rarely show what actually happens

• but they can help the analyst understand basic processes

• they are good for the initiation of the analyst

Fact finding techniques:

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Observation:

• enables the analyst to gain information that could not be obtained with other techniques

• first-hand information about what actually happens

• difficult to create conditions where the analyst is allowed to observe without inferring with events

• potential “spy” effect

Fact finding techniques:

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Techniques to organise the details collected:

• Documenting how people work means analysing decisions and procedures

• This requires a number of steps:

– determine what the conditions are– identify the relevant decision variables– eg: the payment of an invoice can be Authorised or Unauthorised– identify the actions that should follow when conditions are met– graphically represent the procedures resulting using decision trees,

decision tables or Structured English

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What are they used for?

• they are Process Description Tools

• used for the determination of systems requirements

• especially in the case of complex / multi-criteria decision situations

• They are used by systems analyst to document such situations and communicate with users

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What is specific about them?

• they are aimed at enabling analysts to lift any ambiguity regarding important decisions to be made by the system

• they enable them to show the users for confirmation in a way that users can understand

• they can be processes directly by special code-generating tools called CASE tools - thereby facilitating / speeding up programming

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Decision Trees:

• a decision tree is a graphical way to represent a sequence of decisions and actions

• it shows which conditions to consider first, second etc...; ie it helps to visualise the process to be followed to reach a good decision

• it also shows the relationships between each condition and the resulting actions

• It is very program-like in its format

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Decision Trees:

• Example of a decision tree with two layers of conditions and four different possible outcomes

RootCondition

Condition

Condition

Condition

Condition

Condition Action

Action

Action

Action

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Example of decision tree:

• Discount authorisation in a company:

if payment was not made within 10 days, the customer pays the full amount

if payment was made within 10 days, some discount may be granted

if the amount in dollars is below £ 5000 the customer pays the full amount

if the amount in dollars is between £ 5000 and £ 10000, 2% discount is granted

if the amount is over £ 10000, 3% discount is given

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Solution:

How muchdiscount??

Within 10days

Longer than10 days

Over £10000

Between £5000and £10000

Below £5000

2% discount

3% discount

Full amount

Full amount

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Usefulness of Decision trees:• good at highlighting the sequence of business decisions

• effective to describe business problems with many conditions

• enable the analysts to verify the accuracy of their understanding of processes by showing their DT to users

• However, Decision Trees can become overly complex when many interlinked processes

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Decision tables:

• it is matrix of rows and columns that shows conditions and actions

• it is made up of four categories:– condition statements

– condition entries

– action statements

– actions entries

• it is like a decision tree, but there is no sequence - It applies covers all situations

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C1: Patient has basic health insuranceC2: Patient has social health insurance

A1: Pay amount of office callA2: Pay nothingA3: Pay full amount for services

1 2 3 4

Y N Y NN Y Y N

X X X X

Condition Decision Rules

Decision tables:

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Different forms of Decision Tables:

• table entries can take a different form

• limited-entry form use entries like Yes, No and X

• extended-entry form use actual descriptions of actions and conditions

• mixed-entry form (combination of previous forms)

• the ELSE form aims at omitting repetition (ie: ELSE = any other conditions that leads to an action)

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Example:

• Sales reps can get extra bonus when they sell our higher margin goods

• Extra bonus is paid up to a maximum of £2000 per year

• It is paid 1 % up to £5000 ordered and 2% above £5000

• In any case, reps receive a letter of congratulation when they take orders larger than £ 5000

• When they sell high margin goods, reps also enter a monthly draw for a dinner in town

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Structured English:• additional method to overcome problems of ambiguous language in

stating requirements

• it uses narrative statements to describe procedures, conditions and actions

• analyst lists the steps in the order in which they must be taken until entire procedure is stated

• procedures consist of:– sequence structures

– decision structures

– iteration structures

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Components of Structured English:

• sequence structures:– are single steps or actions included in a process

– individually, they do not depend upon any condition

– a procedure typically consist of several sequences

example: buying a book

1 - pick the desired book

2 - take the book to the cash desk

3 - pay for the book

4 - leave the store

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• Decision structures are used to describe the conditions which regulate the execution of the sequences

example - buying a book – the condition for the execution of the sequence is that a desirable book is found

IF a desirable book is found, THEN take the book to the cash desk pay for it leave the storeOTHERWISE (or ELSE) do not take the book to cash desk check the next book

Components of Structured English:

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• Iteration structures are structures that are repeated 1- while a condition is true or 2 - until a condition becomes true

example - buying a book:DO WHILE more books to examine read the title of the book select or reject itEND DO

DO UNTIL desired book found pick a book read the title

select or rejectEND DO

Components of Structured English:

} 1

} 2

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Real example - Accounts Payable Processing:

Do until all invoices are processed

If invoice is signed then

log invoice - pay amount

Else

If merchandise was not accepted

Reject invoice

End if

If invoice is not priced properly

Correct invoice amount

log invoice - Pay new amount

End if

End if

End Do

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Structured analysis of systems requirements:

• Additional techniques to document requirements of new systems

attempt to tackle two problems below:

• Would two analysts identify the same set of requirements when they independently study the same system???

• How well defined are the applications that analysts get to investigate by talking to users, studying current systems etc.??

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Tentative answers:1 - If one can say that a systems analysis report is either

right or wrong then, the 2 analysts should come up with the same requirements. But is this true?

2 - The settings in which ISs must be developed are ill-defined and systems themselves are not stable.

Two different analysts are very unlikely to get to observe the same situations

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Structured Analysis as part of the solution:

• manageable and logical way to learn and report about a system

• the method attempts to “structure the requirement determination process”

• It is based on the use of:

– Structured English– Graphic symbols:– Data dictionary– Procedure and process description– Rules and standards for documenting systems

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Data Flow Analysis:

• Major part of structured analysis involves Data Flow Analysis:

• What processes make up the system?

• What data are used in each process?

• What data are stored?

• What data enter and leave the system?

The emphasis is clearly on identifying Data Flows.

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Tools for Data Flow Analysis:1 - Data flow Diagram: central tool for DFA on the basis of which

the components of the system are later developed

2 - Data Dictionary: consists of the name, description, aliases, contents and organisation of every data item in the system and the processes in which they are used

3 - Data Structure Diagram: relations between the different entities in the system

4 - Structure Chart: relations between processing modules in a computer system

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Notation used for DFDs (according to Yourdon):

Data Flows look like:

Processes look like:

Sources or destinations of data look like:

Data stores look like:

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Example of DFD:

Source Destinat.Process 1

Process 2 Data Store

Data Flow 1

Data Flow 2

Data Flow 4

Data Flow 5Data Flow 3

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Additional symbols used in Data Flow Diagrams:

Three categories of symbols

• Media symbols = actual devices or objects that are used to display, store or print data

• Processing symbols = processes that are used in the system; they can be either automatic or manual

• Descriptive symbols: used to show the direction of the flows and to make DFDs more readable

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Rules in creating Data Flow Diagrams:

Employee

AccountsReceivable

Dpt.

Create newmemberAccount

Employee

Member accounts

generateemployee

bankstatements

freezeaccountnumber

bank statement

employeestatus

frozen accountnotificationmodified

accountstatus

existingaccount

membershipapplication

employeeid and address

1

2

3

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Employee

AccountsReceivable

Dpt.

Create newmemberAccount

Employee

Member accounts

generateemployee

bankstatements

freezeaccountnumber

bank statement

employeestatus

frozen accountnotificationmodified

accountstatus

existingaccount

membershipapplication

employeeid and address

1

2

3

Process #1: Black hole !!

Process #2: Miracle!!

Process #3: Gray hole!!

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Rules in creating Data Flow Diagrams:

Routetransaction

Customer

ProcessPayment

Processorder

Processcomplaint

customertransaction

order

payment

complaint

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Rules in creating Data Flow Diagrams:

CustomerProcessPayment

Processorder

Processcomplaint

order

payment

complaint

Processes that do not make decisionsor change incoming data should be eliminated

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Rules in creating Data Flow Diagrams:

PhoneCompany

Pay phonebill

Invoice

Itemised calls statement

Invoice and itemisedcalls statement

If two flows always travel together, they should be shown as a simpledata flow

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Rules in creating Data Flow Diagrams: Customer

Processorder

Credit VouchersDue

Payments

Bill and creditvoucher

Creditreceipt

Customer

Processorder

Credit VouchersDue

Payments

Bill and creditvoucher

Customerreceipt

Approvedcredit voucher

Sale

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Illegal Data flows:

You need a ProcessBetween all these elements:

“ All data flows must either end or finish at a process “

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Additional rules:• Only processes can be connected to a data store

• A data flow from a data store to a process means that the process USES the data

• A data flow from a process to a data store means that the process UPDATES the data stored - ie:

– it adds new records

– it deletes existing records

– it changes existing records

• try avoid crossing lines on a DFD, eg by placing your data stores in the middle of the page

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Example of DFD:• Analysis of Accounts payable

• Elements (data sources or destinations) in the diagram are:– vendors

– vendor data

– accounts payable data

• Flows are:– invoice

– check

– mailing address

– balance

• First level = only one process, here Accounts Payable

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Solution of the DFD for Accounts payable

Accounts payable

VendorAccountspayable

processingVendor data

Balance

Vendor invoice

Cheque

Mailing address

This the level 1 DFD also called Context Diagram

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Steps in solving the Decision Table are:

1 - Identify the conditions and values

2 - determine the maximum number of rules

3 - identify the possible actions

4 - Enter all possible rules

5 - Define the actions for each rule

6 - Verify the accuracy of the table with users

7 - Simplify the table by eliminating impossible and indifferent conditions

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Steps in solving the decision table:

1 - Identify the conditions relevant to the case and the values that can be assumed:

Data Attributes and conditions:

1 - Account type: R = Regular rate S = Split Rate

2 - Insurance Y = Yes N = No

3 - Balance dropped below £25 during month? Y = Yes N = No

4 - Average daily balance 1 = £ 0 to £ 24.99 2 = £ 25 to £ 500 3 = £ 500.01 to £ 2,000 4 = more than £2,000

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2 - Determine the maximum number of rules:

that gives you the number of “solutions” of the problem - like throwing dice

Condition # 1: 2 values

Condition # 2: 2 values

Condition # 3: 2 values

Condition # 4: 4 values

Number of rules in DT = 2 * 2 * 2 * 4 = 32

Steps in solving the decision table:

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3 - Identify the possible actions:

• Pay no dividend

• Pay 5.75% / 4 on the full balance of the account as a quarterly dividend

• Pay 6 % / 4 on the full balance of the account as a quarterly dividend

• Pay 6% / 12 on the balance up to £ 500 as a monthly dividend

• Pay 6.5% / 12 on the balance between £ 500.01 and £ 2,000 as a monthly dividend

• Pay 7% / 12 on the balance over £ 2,000 as a monthly dividend

Steps in solving the decision table:

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Create the framework of the Decision Table:

• you know how many conditions there are

• you know how many actions there are

• you know how many rules there are

• format your table accordingly with:– the condition statements

– the action statements

– leave the rest blank

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4 - enter all possible rules:

a - alternate the possible values for the first variable

b - cover each repeated pattern of the first condition with each of the values of the second condition in turn

c - repeat previous step with each further condition

Steps in solving the decision table:

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5 - Define the action for each rule:

use X to mark the appropriate actions in the table for each of the combination of rules

Add another action in the table to mark the situation that are impossible (ie that cannot happen)

Use ??? to signal situations where you do not know what should happen. These will require that you go back to the users and ask them - c.f.: step 6

Steps in solving the decision table:

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7 - Simplify the Decision Table:

The table is now complete and correct

However, the table is not ready for programmers yet

a - eliminate impossible situations

b - look for indifferent conditions (ie conditions that do not affect the decision)

– find a set of rules for which the actions are identical and one and only one condition changes and takes all possible values

– consolidate that set of rules by replacing the value of the indifferent condition by a minus sign - the indifferent symbol

Steps in solving the decision table:

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Narrative for Sales Order system

• Customer submits an order. The ‘get order’ process either sends a reject notice to the client or a picking list to the warehouse

• A completed order notice is sent from the warehouse and is input to the ‘create invoice’ process which outputs an invoice (one copy to the client and one to accounts receivable data store)

• Clients make payments which are processed by the ‘process payment ’ process. This process requires invoice details from accounts receivable and the payment. It also outputs payment details to the accounts receivable datastore, commissions to the sales reps file, bank deposits to the bank and cash receipts entries to the Accounting department

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Data Dictionary:

• catalogue of all elements in a system

• list of all the elements composing the data flowing through the system:

– data flows

– data stores

– data processes

• data dictionary provides both descriptions of these elements and details of where they are used in the system

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Importance of the Data Dictionary:

• It is developed as a complement to the Data Flow Analysis of the system:

– legend of the diagrams

– more information on the data elements

– names and titles of key informants

• assists the analyst in determining the system’s requirements

• also used in the design phase for reference to such details as ‘data length’, ‘transaction volume’, etc...

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Use of the Data Dictionary in development and maintenance

Analysts use the Data Dictionary in five main ways:

• to manage the details of large systems

• to communication a common meaning for all system elements

• to document the features of the system

• to facilitate the identification of the areas where changes are required

• to locate errors and omissions

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Manage details:

• large systems have huge volumes of documentation: reports, input / output documents..

• Such volume of data far exceeds the capacity of human memory

• Conventional means of storage would not allow the organised retrieval of these data

• Newer development environments include automated data dictionaries

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Communicate meaning:• Data dictionaries ensure common meaning for all

people involved

• many different way to define even simple things like ‘invoice’ or ‘total amount’

• no meaning should be assumed and when clarified, it should be documented for everyone to see

• Every member of a team has access to the DD

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Document system features:• the Data dictionary has a long term use too as it will be used

for the maintenance of the system

• it will also be used in the evaluation of the existing system when the system gets older

• it will provide a better basis for the development of a replacement system (it will be reusable)

• it can become a company-wide data dictionary to be used across systems

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Facilitate analysis:• to help determine whether new features or changes are

needed in a system

• to enable analysts to answer a number of questions regarding:

– the nature of transactions (what business activities are carried out)– example of potential inquiries (how will the data be retrieved and

processed)– output and report generation (how will the data be presented)– files and databases required– system capacity (what volume of transactions will be treated)

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Locate errors and omissions:

• to trace conflicting data flow descriptions

• to discover processes that neither receive input nor generate output

• to identify data stores that are never updated

• some automated dictionaries will actually scan for inconsistencies and produce an error report

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What does a DD look like?• data dictionaries contain two types of descriptions

• data items:– also called fields or elementary item

– smallest unit of analysis

– building blocks for all other data in the system

– eg: invoice number, date, amount due...

• data structures:– set of related data items describing a component of the system

– eg: Invoice is a data structure made up of a number, date, amount due....

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Describing data elements:

• data names - (ie a meaningful name)

• Data description (states what the item represents)

• Aliases - other possible names

• Length - the space required to store one item

• Possible data values - the range of values the item can take

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Strategic use of Database Technology:

• The case for Strategic Information Systems (SIS)

• Some examples of successful applications

• A close look at database applications

• Strategic uses of Databases

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Information systems can be strategic??

• After the industrial revolution, the information revolution (Porter and Millar, HBR 1985)

• Computers have become so flexible that there is no limit to the range of tasks they can support

• This was called “the third era” of computer use (J F Rockart, 1983)

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Observations about the 3rd era:

• ability to use information systems technology is essential for success

• some companies apply IT with great benefit; others make no progress at all

• “reactive approach” to IT no longer works– too much novelty too fast

– technology more and more powerful

• role of business managers in introducing IT has become paramount

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Managing Information systems for competitive

advantage• The way companies use IT actually makes a difference

• Application of IT must be managed properly like other assets of the company

• Information technology is changing the way companies operate internally and externally– it alters industry structures

– it supports differentiation strategies

– it opens new businesses

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Strategic Information Systems:

• Described in IT journals in the early 80s

• Difficult to define an SIS

• Even more difficult to plan for one

• Most of the research has concentrated on analysing existing instances of SIS

• Some unconvincing attempts to come up with a method to generate SIS

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Formal Techniques to exploit IT

• Business System Planning (BSP): IBM in the 1970s– 13 different steps– very cumbersome, expensive and long

• Strategic Planning for IT– to provide a solid technical foundation– alignment with the corporate strategy

• Application Generator: C. Wisemann– aimed at outside opportunities– up to 100 potential applications per company

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Rockart’s CSF method:• Identification of a hierarchy of performance measures

that lead to identification of Critical Factors and Issues that will determine a business’ success

The business mission statement

The business vision statement

multiple business goals

multiple business objectives for each goal

multiple CSFs for each objective

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Porter’s Competitive Analysis (1980)

• based on the “five forces” matrix

• scope includes the entire business

• According to the framework, organisations' ability to compete is determined by:

The threat of new competitors

The threat of substitute products or services

The bargaining power of customers

The bargaining power of suppliers

The rivalry amongst existing competitors

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McFarlan and McKenney’s framework:

High

Low

Strategic Potentialof IS/IT

Strategic Importanceof Current IS/IT

HighLow

Turnaround

Support

Strategic

Factory

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McFarlan and McKenney’s framework:

High

Low

Strategic Potentialof IS/IT

Strategic Importanceof Current IS/IT

HighLow

EducationFarming

Cement FactoryFuneral Homes

NewspaperBanksTravel agents

Retail businessRestaurants

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Well-known examples:

• SABRE (American Airlines): first effective electronic reservation systems in the US

• simple one-line database application

• took a long time to justify the investment

• competitive value of system still felt today

• in 1988 AA were making more money out of SABRE than out of flying air planes

Page 218: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

• American Hospital Supply Corporation (AHSC): system whereby customers can directly re-order their supplies from terminals located in their hospitals

• Successful because it enabled AHSC’s customers to cut their costs of administration

• originally meant as an INTERNAL systems by AHSC and extended to one main customer

Well-known examples:

Page 219: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

• Digital Equipment Corporation (DEC): an expert system that supports the process of designing and specifying large computer systems

• Xcom is based on the experience of the best specialists in DEC

• it eliminated a bottle-neck in DEC’s processes

• additional gains in customers satisfaction were obtained as a result

Well-known examples:

Page 220: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Analysis of existing SIS:

• SIS were never intended to be strategic

• They rarely involve radically new technology

• They rarely originate in the IT function

• They are generally based on a “first mover” advantage, but there have been some striking counter-examples

• Ability to handle huge amounts of information is often main factor - ie: use of DBs

Page 221: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

A close look at Database applications:

• More and more applications involve databases

• on-line systems as opposed to batch processing

• new concepts (relational databases) make DBs much faster

• available on more and more platforms (UNIX, PCs...)

• Databases are becoming cheaper to manage and easier to maintain

Page 222: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

• Databases are perfect to handle the large amounts of data which companies require (+DW)

• Databases make distributed computing and data sharing easier

• Software vendors developed new development environments which include a DB engine– Oracle + 4th GL– INGRES + 4th GL– All PC products for Windows (Access, Paradox, Foxpro...)– Visual Basic 4 + Jet engine

A close look at Database applications:

Page 223: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Strategic Uses of DBs:

• at a technical level, DBs are just a set of functionalities - ie data storage and retrieval

• databases have far greater potential than just mere record stores

• strategic applications arise when people try to creatively imagine how these functionalities could be used by a business

• DBs are not looked at as support applications anymore, they can add value for the organisation or its customers

Page 224: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Potential areas of DB use:

1 - to cut administrative costs

2 - to serve customers better

3 - to enter new product areas

4 - to increase sales volume

5 - to improve decision making

Page 225: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

To cut down administrative costs:

• Reduction in staff costs not a very strategic application of DBs

• But, significant competitive advantage if company’s cost structure is greatly improved

• eg: UK Department of Social Security computerised their paper files:

– system must handle 60 million records– can deliver benefit cheques within 24 hours– it cut down the required work force by 20,000 staff– so costly (£ 2,000 millions) that it is unlikely to pay for itself

Page 226: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

To serve customers better:

• this has become a popular (and necessary) strategy

• It can involve developing new services that the customer may require (lodging cheques in an ATM)

• or making an existing service more practical (speeding up the payment of social benefits)

• eg: British Rail’s Computerised Assisted Timetable Enquiry system (CATE)

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To enter a new product area:

• Specific DBs are required to assist in reaching potential customers

• sometimes by-product of implementing another DB

• eg: Marks and Spencer built their first customer database to support their credit card system– later expanded to the financial area

– use their database to select and to contact potential customers

• once DBs have been developed, they can be sold to other organisations (eg: Time, Newsweek...)

Page 228: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

To increase sales volume:

• most companies have the opportunity to collect loads of data about their customers - few do it

• experience with DBs has shown that they have a great potential in improving a company’s knowledge of its customer base

• eg: Aer Lingus have compiled typical profiles of their customers per period and per route

Page 229: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

• eg: Hewlett Packard's customer Database:

– each salesrep was equipped with a portable with MODEM

– applications available include address book, time and expense recording systems, a word processor and access to corporate DB

– time saved by salesreps is spent with customers

– sales increased immediately

– they now have the perfect customer DB and started telemarketing

To increase sales volume - another example

Page 230: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Customer databases to improve marketing decision

making:• DBs enable organisations to store very specific information

re thousands of customers

• information can be classified according to socio-economic criteria (eg: age, geographical location

• mailings can then be more targeted and efficient

• new products launch can even result from such information

Page 231: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

How to obtain customer information:

• customer DBs can be compiled from four main sources:

sales invoices

sales reps

published documents / advertising

external databases - information services

Page 232: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Sales Invoices:• Always been a source of information on customers

• Now, computerised invoicing applications

• They usually record– names of companies / contacts – address– dates and amount / quantity / references of sales– discounts and other terms and conditions– name of the salesrep

• Analyses arising from invoices are– sales territory and analysis of salesforce– customer profiles – seasonality

Page 233: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Information collected by the sales force:

• Commonly under-utilised by organisations

• Salesreps very seldom on the premises – information delivered in bulk– too late after the event

• Communication problem between HQ and the “field” people

• Creative use of portables + networks + EDI can yield huge benefits (Northern Telecom)

Page 234: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Published documents / advertising:

• A unit within the organisation scans the press systematically for opportunities

• Not an option for small companies

• Very important for state markets and community equipment

• Competitor scanning is also becoming a common activity

Page 235: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

External Databases including the WWW

• More and more of sources of information are available

• From simple reference databases (Lexis [Law] information system) to on-line up-to-the-minute services regarding the stock markets

• Companies have to subscribe to the service and pay a fee per inquiry

• Connection has become trivial with Internet

• eg: Banks, Marketing organisations, advertising agencies etc...

Page 236: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Computers and the Law:

• according to the “IS Analyser” :

As companies make more use of information systems to run their businesses, sell services and add value to their goods, there is greater likelihood that poor information practices will lead to harm to themselves or their customers

• Legislation dealing with the role of computers in business has become a necessity

Page 237: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Legal requirements for databases:

• Since 1987, Data Protection Act

• “to protect the privacy of individuals relative to personal data which is processed automatically”

• Personal data means information related to a living individual who can be identified from the data itself or other information held

• Bill gives right to the people to access “their” information and duties to the people who hold personal information

Page 238: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Obligations of information holders:

• implement and maintain computer security procedures

• obtain and process data fairly

• keep data accurate

• keep data for specified and lawful purposes

• keep data confidential

• keep only relevant data

• delete redundant data promptly

• remove data from lists upon request

Page 239: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

• they may have to register under certain conditions:

1 - if they hold certain kinds of information:– about racial origin

– about political opinions

– about physical and mental health

– about criminal convictions

2 - if they are:– public authorities, financial institutions, credit reference

agencies, direct marketing agencies or data processors

Obligations of information holders:

Page 240: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Rights of people upon whom information is held:

• have the right to find out about any record concerning them

• have free access to records of information concerning themselves

• have right to trigger legal intervention to obtain that inaccurate data is corrected or removed

• have to the right to refuse to be included in marketing lists which might arise from the database

Page 241: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Managing IT investments

• Allocation of resources to selected projects

• Application portfolio contains list of potential systems

• Limited resources mean that systems must be evaluated in terms of their business potential– justifying investment

– allocating priorities

– determine how the expected benefits will impact the business overall (+review of these)

Page 242: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Evaluating IS investment

• Little consensus on how to do it

• Total consensus that it is not done properly– 70% of organisations have no formal process

– only 30% of projects’ outcome are reviewed

• Variety of types of benefits suggests that multiplicity of methods id required

• Old fashion financial oriented methods less and less appropriate

80% of IT directors admit that cost/benefits analyses are“a fiction” in relation to IT projects

Page 243: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Characteristics of IT investments

• Technology investment does not really have a return on investment (unless it strictly replaces another older system)

• Many investments in infrastructure cannot be linked to a specific application and their potential is not exhausted by one project

• But technology is not always scaleable (purchase in increments)

• Additional development costs incurred within functional areas are rarely taken into account

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• Identifying and quantifying benefits is also difficult

• Consider the following three types of applications:– Substitutive to improve efficiency

– Complementary to improve effectiveness

– Innovative to obtain and preserve competitive advantage

• These different types of applications require different methods

Characteristics of IT investments

Page 245: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Generic Methods

• Traditional cost/benefit analysis - good at measuring improvements in efficiency

• Value Linking - good to estimate improvements in business performance

• Value acceleration - to model the positive (non £) consequences of saving time in business processes

• Value restructuring - to plan for the productivity resulting from a combination of better systems and other fundamental change

• Innovation evaluation - to take into account the additional revenues that can be obtained from extension of business to new activities

See figure 10.1

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Examples of targets for these Methods

• Traditional cost/benefit analysis

• Value Linking

• Value acceleration

• Value restructuring

• Innovation evaluation

Savings resulting fromautomation

More accurate billing means less time spent in correcting mistakes

Acceleration of order processing internally means more time for negotiating with suppliers for the buyers

Support given by systemsin implementing change

IT based plan to developtotally new activities

Page 247: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Summary• Costs and benefits should be appraised in both IT and

business domains

• 5 different categories of benefits have been put forward

• Overall value of project is combination of all these

• Long term and short terms benefits must be included

• Not possible to convert all intangibles to financial figures (spurious)

• However crucial to establish how intangibles will be measured and monitored

• Portfolio Analysis can be used as guide

Page 248: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Portfolio Analysis

High

Low

Potentialcontribution

of IS/IT applicationto achieving future

business goals

Degree of dependenceof the business on IS/IT application

in achieving overall business objectives

High Low

Support - Safe

Strategic -Attack

Key Operational - Explore

High Potential -Beware

Page 249: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Lessons from the Portfolio approach

• Quantitative justification easier in key operational and support quadrant

• Reliance on single method will result in only one type of application to be developed

• The way IS is regarded and managed in the organisation will be reflected in the way IT investments are justified

(see figure 10.2)

Page 250: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Support• Given the aim to improve efficiency, financial evaluation

should be used

• benefits should be quantified and a financial argument made

• Additional arguments might be relevant (eg: staff morale) - other methods to be used for those

• Potential benefits must be evaluated before any resource is committed

• To compete against other projects, a support application must show a good return on investment especially when scarce resources are involved

Page 251: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Key operational

• Some important arguments cannot be converted into financial arguments

• Not suitable to estimate all benefits prior to any resource allocation or cost determination

• most economic solution may not be the most effective

• Critical failure effect if systems do not do enough

• Some freedom must be given to each business unit to initiate such projects even when the economic rationale is not obvious to an outsider

• But design and implementation must be undertaken by central IS/IT

Page 252: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Strategic Applications

• Very important applications - critical in achieving future business objectives

• Cost / benefits should be evaluated in terms of their order of magnitude

• Reasons to go ahead will remain intangible (linked to CSFs)

• Attention of top management is required to ensure that objectives are met and resources are available

• Centralised processes is best with a task force approach

Page 253: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

High potential Applications

• Benefits are unknown! Only potential benefits can be anticipated

• Projects should be treated as R&D projects (on a separate budget)

• Project champion arbitrates between spending too little and spending too much (Hayes’ model)

• Iterative process of developing a bit and evaluating the results then re allocating some resources etc...

Page 254: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Assessment of Priorities

• Priority score should be a compound measure of:

• what is the most important - Benefit

• What can be done - Resources

• What is likely to succeed - Risks

• This final factor must be added so that not all projects undertaken are high risk = nothing achieved

Page 255: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Application to the different types of systems

• Support: greatest “doable” economic benefit• strategic: use scoring framework as in fig 10.3

– business objectives can be ranked

– division of score per person-year of scare resource means contribution can be maximised

– must however not be used mechanistically

• High potential: more difficult to prioritise– link to CSFs often tenuous

– strength of champion’s position and support will count

• Key operational systems: different framework– economic rationale

– CSF

– risk to current business

– infrastructure improvements

Page 256: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Managing the IS department:

• Dilemmas in managing IT:– limited to the administration of systems

– searching for new opportunities to develop the use of IT

• Success of the IT function is often measured based on the operation of existing systems

• Adaptability and creativity are not assessed

• Neither is the efficiency of resource usage

Page 257: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Tasks of IS

• IS delivers a service to the rest of the organisation - it is a support department

• IS is in charge of managing the computer resources and the technology

• IS must plan for future needs on behalf of the whole organisation

• IS must develop the new systems that will be help the organisation in the future

Page 258: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

IS as a service department

• supporting end-users - answering their requests

• training users

• provide a secure environment

• providing advice on how to tackle problems in the future

There are a number of strategies to fulfil this role

Page 259: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Different philosophies of Network Management:

1 - Centralised DP:

• one company = one computer

• one department does all the processing

2 - Decentralised DP:

• each individual function has own computer with home made rules and procedures

3 - Distributed DP (DDP):

• somewhere in between

• various computers available throughout the company

• all linked together

Page 260: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

+/- of the different philosophies:

1 - Centralised DP:

• easy to maximise use of computer and to control usage

• flexibility for user is restricted

2 - Decentralised DP:

• difficult to maintain and share corporate data (compatibility of software, hardware...?)

3 - Distributed DP (DDP):

• more difficult to manage

• does address the difficulties of both philosophies

Page 261: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Traditional IS

• computing is a centralised activity managed by the IS department

• functional areas have no freedom in relation to the selection or the usage of IT

• functional areas have no budget for computing

• the IT architecture developed in the organisation is centralised as well

Page 262: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

End-user computing

• Users / managers are active in determining the systems they require

• They are active in specifying the requirements for these applications

• They may even develop the applications themselves (if skilled enough)

• They have a specific budget within their functional area to accomplish this

• They may be supported by the IS department through an Information Centre

Page 263: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Problems with EUC:

• less transparency in the IS spending (up to 50% in “hidden” costs)

• more difficulty in integrating inter-departmental systems

• possibility that individual buyers make wrong choices

• Loss of economies of scale

Page 264: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Problems with EUD

• No overall view of business systems

• no standards for development and documentation

• likely duplication of efforts and data

• likelihood of loss of critical knowledge

• risk of local users “re-inventing the wheel”

Page 265: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Advantages of EUC

• faster application development / implementation

• increased chance of getting requirements right

• users become more expert at using computing resources

• productivity increases at individual user level

• reduction of the “application backlog”

Page 266: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Outsourcing

• Transfer the responsibility for IS to an outside organisation (various degrees)

• Use a computer service provider for one or more applications

• outsource some development work

• Do without an IT department and depend entirely upon outside specialists

• Saves money but with major consequences for control and strategic developments

Page 267: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Historical evolution of IS

• Stage of growth model (Nolan)

• All organisations go through similar stages

• EUC emerges in stage 2

• EUC must be carefully managed through the other stages

• Failure to manage EUC means organisation does not go into later stages

• Evolution is basically a cycle of phases of control, EUC and outsourcing

Page 268: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Dealing with IT costs

• Allocating or charging out costs

• Seen as an administrative or accounting procedural matter

• can influence the selection of and management of IT investments and budget

• Who pays for IS projects and who is responsible determines how applications are cost justified

• Also accountability for failure and over spending

Page 269: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

The Chargeback system

• Unpopular at the best of times

• users see it as a pricing mechanism: how expensive should IT be?

• Transfer pricing for buying and selling IT products and services

• All boils down to status of IS department and whether functional areas have access to a free IS market

Page 270: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Free Market?

• Have functional areas their own budget?

• Is IS an independent profit centre?

• Is IS in competition with other suppliers?

• Can IS refuse unprofitable work?

• Who prepares the IS budgets?

• What cost drivers to use?

Page 271: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Calculating IS usage

• Traditionally, CPU time and other very technical parameters

• More fair to the user to use more visible and business-like measures:– number of transactions

– number of screens viewed per session

– …

• Matter of business policy!!

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Vision of the status of IS

• Earl argues that charge-out system must reflect the role of IS as component of the business:

• service centre: IS service not chargeable

• cost centre: users are charged with costs representing the resources consumed (IT costs are recovered)

• Profit centre: users pay a market price (IS department can have its own revenues + bid for outside work)

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Implications for charge-out system

• Cost centre: charging method based on average/standard costs (e.g. network)

• Profit centre = open market - players can accept / refuse work based on availability of better offer

• First step to outsourcing??

• Hybrid method may offer best solution,– charges determined by the nature of each application

• but is difficult to implement

Page 274: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Socrate - Buying systems instead of developing them

• Reservation System for the French National Railroads (SNCF)

• To be implemented at a set deadline at the same time as the launch of the Atlantic TGV

• Ambitious attempt to develop a Global Distribution System (GDS) for rail transportation

• Very large development project– current system obsolete

– lack of confidence in internal development (previous failure)

• Why not buy SABRE?

Page 275: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Story of a Disaster

• Launch January 18th 1993

• Million of customers stranded

• Queues longer than ever before

• ghost trains

• missing towns (eg Rouen / 400,000 inhabitants)

• Clerks went on strike

• traffic decrease by 7% in 1997!

Page 276: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

The real story

• Difficult managerial decision

• difficult project technically (never done before)

• Other factors (increased competition) explain the bad results of 1993

• Reason of the failure were largely external to the project

• No support from top management

• SNCF is important and irreplaceable service

Page 277: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Why buy SABRE?• Current system has reached the end of the road• bad experiences with semi-state bodies developing large

systems• GDSs are enormous packages - Socrate was expected to

– take 500 man years to create– add up to a million lines of code– cost around £150 million

• Train industry is very specific => outsourcing not an option• Lack of political support for European collaboration• SABRE provided a good basis for what was needed - service

+ yield management

Page 278: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Development

• Joint venture between AMR and SNCF

• gradual transfer of responsibility and knowledge

• overshot budget by 20%

• was ready just about on time

• systems has now been sold to SNCB, SNCS and other European operators

• Users and customers not involved in development

• Training was minimum

Page 279: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Greatest Problems

• Bad analysis of requirements

• Underestimation of the complexity of the problems raised (eg: exceptions)

• Not consideration given to training needs

• Lack of understanding of the implications of the culture and structure of the company (eg: databases)

• Appalling communication with the public

So Socrate…..success or failure????

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AIMS OF PROJECT MANAGEMENT:

• Ensure the respect of dead-lines

• Ensure the respect of users’ requirements

• Ensure the quality of the systems

• Meet the target costs

Module 4: Problems with Information Systems DevelopmentModule 4: Problems with Information Systems Development

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FEASIBILITY STUDY:

• Make sure that vendor and client organisations will be able to carry out the project in the best conditions

• Is the project worth pursuing - what benefits will it deliver to the organisation

Crucial FROM THE CUSTOMER’S POINT OF VIEW as well as from the vendor’s point of view

Module 4: Problems with Information Systems DevelopmentModule 4: Problems with Information Systems Development

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MANAGEMENT TOOLS (1):

• The development effort is broken down into tasks and sub-tasks

• Each task is documented and assessed for duration and difficulty

• All tasks are then built into a Worksheet

• The resources are allocated

• Dead-lines and critical dates are checked

Module 4: Problems with Information Systems DevelopmentModule 4: Problems with Information Systems Development

Page 283: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

• Developers submit detailed time sheets on a weekly basis

• All time sheets are compiled into a spreadsheet

• Reviewed in a weekly progress meeting

• Any task off target is re-allocated and rescheduled

MANAGEMENT TOOLS (2)

Module 4: Problems with Information Systems DevelopmentModule 4: Problems with Information Systems Development

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most important from the customer point of view:

• Regular meetings are held between the project managers on both sides:– Ensure the respect of the specifications

– Co-ordinate the phases

– Plan for the availability of personnel

• Senior Management From Both Companies should try to Meet / Talk at Least Once a Month

MANAGEMENT TOOLS (3)

Module 4: Problems with Information Systems DevelopmentModule 4: Problems with Information Systems Development

Page 285: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Protection of Information Resources

• Modern network-based environments require the application of basic security principles to distributed environments.

• “An open, secure system is a contradiction in terms” (datapro, 1994).

• any data flowing through a network or cached temporarily is vulnerable

• as security is implemented, freedom is reduced

Page 286: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Basic principles of security

• Confidentiality

• integrity

• authenticity

• utility - fitness for a purpose

Page 287: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Steps in protecting Distributed Resources

• Identify what you want to protect

• evaluate and determine all possible weaknesses / sources of risk

• constantly review access to IT resources and IT audit procedures

• routinely conduct / update risk analysis of the operation

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Priorities for the Protection of Computer Resources

• Prevention of computer crimes - ie ensuring that information resources are only used as prescribed and by authorised personnel

• disaster planning - pro-actively envisaging what might happen in order to minimise risks

• disaster recovery or “business continuation” - ie ensuring that consequences of crime and accidents will also be minimum so business can resume immediately

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Computer crime:• using computer resources to engage in unauthorised or illegal

acts– stealing money from a bank

– copying and using programs without required licence

• as technology spreads, opportunities for crime increase

• still very loose legal framework means few people are prosecuted

• 80% of crimes are insiders’ jobs (employees)

• most instances are not reported (banks!!!)

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Types of computer crime:

• a very large number of different ways:

– data diddling: unauthorised modification of data

– the Trojan Horse technique: a block of code hidden in a program

– the salami technique: shaving minute amounts to each transaction

– Trapdoor routines: special programs used in the development phase sometimes not removed

– Eavesdropping: spying of data communication between LANs and mainframes for important info

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Recent survey• security problems resulting in financial loss:

– 24% software failure – 12% network failure– 12% virus– 11% computer failure– 7% stolen data– 5% sabotage– 4% network break-in

• Nearly 50% have lost valuable info in last 2 years

• 20 respondents have lost info worth more than £1 million

• 70% say security risks have worsen

• 80% have hired a full time info security director

• 67% have faced viruses in the last year

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Computer related crime

• credit card fraud 96%• telecommunication fraud 96%• staff use of corporate computer for personal use 96%• unauthorised access to company files 95%• cellular phone fraud 95%• unlawful copying of copyright software 90%• theft of information regarding:

– clients 81%– trade secrets 80%– new products 75%– confidential employee information 75%– money 72%

Page 293: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Hackers and Bandits:

• most prolific types of unauthorised activities on computer systems

• a hacker is someone who breaches communication and network security to gain unauthorised access to a central computer

• Hackers are supposed to do it for the fun

• very often not classified as computer crime and not prosecuted

• They can however be tricked by Bandits who give them “bad ideas”

Page 294: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Requirements for identification of computer crime:

A number of conditions have to be demonstrated to enable prosecution of the crime:– knowledge: criminals must have competent knowledge about the

act and be aware of the consequences

– purpose: the must have an underlying purpose, specific intent otherwise, browsing may be merely “electronic trespassing”

– malice: they must be motivated by malice and wish to do harm in some way.

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How to make it easier to trap Hackers:

• have investigation procedures ready to be implemented

• they will aim at freezing the situation and preserving the scene of the crime– prevent further damage to data and programs

– limit the losses incurred

– find out what went wrong

– identify the perpetrator (if any)

– preserve evidence in view of legal action

• in the case of internal threats, publish an internal code of conduct for employees (included in work contract??)

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Why are computers so vulnerable?? - DATA

• data can be stored in pocket size forms (floppy disks, disks, tapes, DAT...)

• electronic data is invisible

• data can leak (electromagnetic waves = tempest)

• data is accessible (can be copied without trace or authority)

• data can get left behind

• centralised data stores can reach high value

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• computers are mythical: users do not behave rationally

• technology is changing faster than companies / people can adapt

• communication and networking are compounding factors

• systems and networks are more and more integrated (open systems)

• processing is more and more distributed

• security standards are still very low

Why are computers so vulnerable?? - COMPUTERS

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Consequences of security breaches

• damage is sometimes unexpected and subtle:– loss of business

– damaged reputation

– compromised organisational secrets

• Primary costs - replacement of destroyed / stolen property

• secondary costs - lost business / revenues

• incidental costs - legal and detrimental costs resulting from damage or settlement

Page 299: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

First step is risk analysis:

• Some general threats to all companies, but each setting is unique => specific analysis

• identify specific worth of organisational assets

• From list of sensitive assets a specific security plan can be designed

• this is best done by an outsider (taking some distance is required) by way of an inquiry:– talking to people

– learning about the company

– writing a report that will convince top management

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steps in security: assessing risks:

• a number of “models” are available for assessing risks

• one example is:

where:– threats are events which cause harm

– vulnerability is the degree of openness of the org.

– asset value is the worth of the assets in danger

• If one component decreases, risks decreases and vice versa

Risk = Threats + Vulnerabilities + Assets values

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Risk analysis techniques:• Subjective analysis = group method where all competent staff review:

– the role of the computer systems

– the nature of the business and the org.

– the history of the company (for previous problems)

– no longer sufficient because not systematic enough

• Quantitative analysis: come up with a figure that should be spent every year by:

– computing the likelihood of each threat

– computing the costs of damage resulting from each threat

– multiplying frequency and impact to obtain the maximum amount that should be spent on protecting the company against each threat

– there are obvious limits to that method too

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Security policy matrix:Impact

10

0

Expectancy

0 10

Plan(What-if?)

Accept Risk(So What...)

Avoid/Escape(What!!!)

Control(What to do...)

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Components of the the security Plan

• physical security

• document security

• personnel security

• hardware security

• software security and logical access control

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Example - physical security

• Plan is aimed at deterring intruders from trying

• efficiency of the barrier is measured by:– the time and cost needed to breach it

– the speed with which intrusions are identified

– the accuracy with which the intruder is identified

– its non-interference with the life of the organisation

• it involves the protection of:– the computers (location, layout of computer centre)

– the services of the computer installation (air conditioning, power, water...)

– fire protection

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Example - document security

• there are a number of documents specific to computer use that are important:– blank pro-formas

– “handle as if..” documents (ie: drafts, mistakes...)

• magnetic documents (ie: disks and tapes) must be registered in an inventory

• tapes must be purged before being re-used

• the life of every computer document should end by its destruction (shredded)

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Who is in charge:

• security is still viewed as an MIS issue

• Co-ordination of security strategy is an MIS issue

• but co-operation is required from all departments / users

• if procedures are not followed, the best strategy is worth nothing

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Security of Networks:

• Security is much easier to implement in M/F environments - ie centralised

• risks increase in LANs and even more in interconnected LANs (WANs)

• Remote access is a great source of risk - eg workstations are left unattended

• Remote access market = $2 billion in 1997

• how to make a network of notebooks safe

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Security with EDI:

• organisations share their IT infrastructure

• paperless nature of transactions requires double care - legal aspects

• prevention, monitoring and recovery must be shared and co-ordinated between the partners

• liability and responsibility could be difficult to establish

• all parties involved must agree on common code of security to ensure “end-to-end” security

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Security with CAD:

• attempt to shorten the value chain of an org.

• design office is linked to outside organisations to contract out work

• design office is on-line to the manufacturing systems

• Integrated system also involves inventory control, finished goods stocks, shop floor control...

Page 310: Quick history of IS Very rapid growth as a profession and an academic discipline early days of “computer is beautiful” lead to mistakes –loads of requests.

Security with Document Image Processing

• Paperless organisation means documents are scanned as soon as they come in

• copies of all documents always available from anywhere

• over-reliance on such systems (inability to handle paper documents) can lead to disaster

• editing facilities make it too easy to “fabricate” documents for fraudulent purposes

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Added difficulties in multi-vendor environments

• most organisations no longer rely on one single platform

• integration means emphasis is on linking these rather than separating them

• password protection can mean that users must remember many different passwords

• encouragement for users to weaken security by using same password or obvious passwords

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Recovery Planning:

• perfect security cannot be achieved and no single countermeasure is completely effective

• security is about reducing the risk to an acceptable level and coping with the consequences– provision must be made for accidents despite countermeasures

– recovery mechanisms are as important as protection

• so security measures should:– operate in conjunction with the corporate life

– be simple and easy to implement

– be cost effective as £££ are scarce for security

– be introduced over a period of time, progressively

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Potential gain from a suitable security strategy:

• improved image:– competitive advantage can be obtained

• enhanced customer confidence:– ensure service continuity– accuracy and privacy of service– safeguard of customer assets

• new products and services:– novel security devices and strategies can be marketed and sold to other

companies– security projects may generate new ideas

• new security features for existing products and services:– can give new life to an old line of products– market opportunities may be lost if security is not up to the standard

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A Strategic Role for IS

• IS as a contributor to organisational value added

• Helping functional areas to develop their contribution

• contributing to developing new specific activities

• e.g. Electronic Commerce

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IS Strategy

IS strategy must be consistent with:

• The organisation’s corporate plan

• its management’s view of the role of IS in the organisation

• its stage of maturity of use and management of IS

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Example of questions that must be addressed

• Where does the IS strategy fit in the wider set of corporate strategies

• what has been the history of IS strategy planning

• what circumstances demand major re-assessment of IS plans

• who might be employed to do the actual planning

• what might an IS strategy contain

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Different organisational circumstances

• Maturity (Nolan)

• Information intensity

• Strategic Importance

• Special circumstances demand extra planning:– major corporate changes (BGE)

– external competitive opportunity or threats

– evolutionary change in IS maturity

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From Planning to Implementing

• Improving IS strategic Planning is primary target of IS and non-IS managers (1994)

• Contents of plans improved over 80s and 90s

• But many IS plans have been left aside nevertheless

• Lack in commitment to implement them - especially top management

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Barriers to implementation

• Lack of top management’s awareness (DP era)

• Credibility gap between between hype and real benefits

• Lack of vision (information not an asset)

• Difficulty in judging / evaluating IS proposals

• Short term focus militates against planning

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Threats resulting from lack of planning

• Loss of control of investment in IT

• Incompatible / inconsistent development of IT usage - eg: UCC

• Conflicts between functional areas

• Systems’ life shorter + greater need for upgrade / maintenance

• Decreasing return on investment

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Good IS planning?

• Impact not instantaneous (2 / 3 years delay in getting benefits)

• Benefits depend on:– starting point (current system’s portfolio)

– opportunities sought

– top management support (champion)

• Proper organisational culture and good relationship between IS and other areas must be developed (eg: BGE)

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Mintzberg’s Grass Root Model

• Planning for IS is everyone’s business

• Balance between formalised strategies and emergent strategies

• Planning process should not only pre-conceive strategies, but also recognise their emergence and intervene when appropriate

• Knowing when to promote change for the sake of adaptation and when to resist it for the sake of internal efficiency

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Adaptive approach to IS planning

• Best opportunities for IS development are often linked to unique assets or resources

• Firms must learn to identify and exploit these

• Hayes (1985):“Firms should acquire technologies and techniques so that workers

and managers gain experience with them and come to understand their capabilities and constraints”

• Organisational structure should be modify in order to foster this process

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Roles in Hayes’ Model• Wizards - corporate experts and librarians for new technologies

• Marriage Brokers - designed to act as intermediaries between users and wizards

• Rich Uncle - manager who pays for seeds so users can develop prototypes

• Weed Puller - top executive who re-evaluate investments and projects and stops or encourage them

• Teacher - educates users about the possibilities offered by technologies and other about the organisation and its products

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Advantages of the Adaptive Approach

• Bottom up process - ideas come from users in close contact with organisational processes

• Top-down approaches are less satisfactory as senior strategists may be unaware of technical possibilities

• Adaptive approach enables focus on specificities of the firm => yield long term edge

• Development of an informal structure of actors involved in strategic idea generation may prove a competitive advantage in its own right

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Topics covered:• Quick history of IS in organisations

– Importance of IS in organisations• Databases - definition - DBMS functions

– Basics of data organisation– relational databases– distributed databases

• Data Modelling: describing relationships - the ERD– Normalisation– SQL

• Strategic uses of databases / Strategic systems• Information Systems development

– Problems with IS– SDLC– Tools and techniques used during SDLC phases– Data flow analysis– Data dictionary– Socrate case study

• Dealing with IT cost • Managing IS investments• Protection of IS resources

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Sample exam question• You are working for the admissions office of a university. The role of your

department is to enroll students into the various courses available in the college. Because the process of registration is getting more and more tedious, your boss has asked you to develop a small database in which first registrations will be keyed in (ie your system is limited to students who register for the first time). The system must hold information about (1) the students, (2) the courses offered by the college (including fees information), (3) the subjects that make up each course, (4) the courses that each student is registering for, (5) the payment(s) made by students and (6) the marks that each student obtains in each subject.

• You are requested to put particular emphasis on the transactional aspect of the system, whereby a student is being registered into a particular course (not forgetting the implications in terms of interface) and to present clear examples of what the data stored in your database should look like.