CSE1720 Semester 1 2005 week 11 / 1 Lecture No. 11

CSE1720 Semester 1 2005 week 11 / 1

Lecture No. 11Lecture No. 11


Lecture ObjectivesLecture Objectives

1. To provide you with some contact with Decision Making Processes and to illustrate support from Computer Technology

2. A brief run through those facilities which are generally classified as Office Automation

3. To look at some of the aspects which need to be addressed in the selection of Hardware and Software


SOME ASPECTS OF THE DECISION PROCESS


Goedels’ TheoremGoedels’ Theorem

“Mathematical statements exist for which no systematic procedure could determine whether they are true or false”

also known as undecidable propositions

Some statements :

‘This statement is a lie’

‘We cannot prove this statement to be true’

Socrates : ‘ What Plato is about to say is false’

Plato : ‘ Socrates has spoken truly’

If the statement is true then it is false

If it is false, it is true. [self referential paradoxes]


The Decision ProcessThe Decision Process

INTELLIGENCE

DESIGN

CHOICE

Determine ConditionsRequiring ManagementAttention/Decision

Develop and AnalysePossible Courses (Alternatives) of Action

Select a particular course of action from the availablealternatives (models, QA,Projections)


Decision MakingDecision Making

• Rules form an important part of the decision-making environment of an organisation (enterprise)

• Rules may be– word of mouth– referenced in a rules manual– embedded in application code (DBMS Integrity)– installed in a separate structure (e.g. law)

Rules affect– hiring and firing procedures– product return policies– sales markdown strategies (January sales ?)– manufacturing methods



• Can there be decisions without rules ?• What conditions, agendas, goals can affect a decision ?• Can the ‘reasons’ for decisions be analysed ?• Is there some way of knowing that the ‘right’ decision was

made ?

• Decisions are frequently associated with ‘action’• Decisions may be about ? ? ?

– Goals of a corporation (enterprise) - for instance diversification or concentration

– Rules of a corporation - e.g. dress code on Fridays to be casual (Telstra)



• Another example is a decision to alter a predictive model. Business and Financial Analysts may change the components or domains for credit risk prediction - any recent examples spring to mind ?

• Decisions can only be implemented on things which can be changed– Is a ‘decision’ to increase sales by say selling solar

panels on Jupiter or Mars really a decision ? Can it be implemented ?



• Making a decision is the function of combining goals and predictive models– The lowering of prices of some products (e.g. K-Mart

sales) is the result of• a goal to maximise sales• a model which relates sales to prices

– The denial of credit by a bank to a loan applicant is the result of

• a goal to minimise loan write-offs• a predictive model which relates selected applicant

attributes (properties) with the likelihood of a loan default



• Without goals there would be difficulty in deciding what course of action to take.

• Without the goal of maximising sales, there is no correct decision concerning product pricing

• Without a predictive model which equates product prices to product sales, there is no clear indication which decision will be most likely to maximise sales



Consider these decision making ‘challenges’

1. The need to automate some decision-making functions

2. The need to ensure consistent decisions

3. Difficulties in analysing how a decision was made

4. Complexities in the predictive model

5. Difficulties in interpreting stated goals (which may change)

6. Instability in the goals

7. Interpersonal dynamics (know any recent examples ?)

8. Fluctuations in the predictive models

9. Conflict between data-driven and model-driven understanding or ‘knowledge (beliefs)’



Business-rule automation tools focus on

1. The need to automate some decision-making functions

2. The need to ensure consistent decisions

Decision analysis tools focus on

3. Difficulties in analysing how a decision was made

4. Complexities in the predictive model

5. Difficulties in interpreting stated goals (which may change)

6. Instability in the goals

Group decision-support tools focus on

7. Interpersonal dynamics



And items 8 and 9 ?

8. Fluctuations in the predictive models

9. Conflict between data-driven and model-driven understanding or ‘knowledge (beliefs)’

more on these later on.

Business rules connect to transaction systems and help to automate decision-making processes which were previously the function and responsibility of persons - the goals are fixed and are explicit.



Decision-analysis tools (software)

Decisions are based on multiple predictive models

There are complex measures of uncertainty or imprecision

The goals may be variable

Decision analysis is related to operations research - the area where– mutually exclusive goals– shared scarce resources

The intention is to maximise profit, stability



Group decision support tools

Consider the situation of many managers of an organisation attempting to arrive at a common decision to– make 300 staff redundant– increase sales to justify no redundancies– increase sales and increase the number of staff– reduce staff but maintain existing sales or improve sales

Interpersonal / political challenges

Anonymous electronic meeting environment

Vote on merit of ideas rather than on identities


The Decision ProcessThe Decision Process

Stage Description

1. Determine objectives, problems

2. Identify courses of action available to

achieve / rectify

3. Collect Information to assess available options

4. Select criteria for evaluation purposes

5. Evaluate information acquired

6. Select preferred course of action / strategy

7. Implement chosen option / strategy

8. Monitor results - post analysis


Decision Support SystemsDecision Support Systems

Characteristics:

Interactive Computer Base Information Systems

Decision Models - Statistical Forecasting, Profiling ...

Management Data Base

OUTPUTS: Information ‘tailored’ to SUPPORT specific

decisions faced by Managers ( Car Industry,

Manufacturing Industry, Farming Industry,

Financial, Accounting etc ...)


Decision Support Systems ComponentsDecision Support Systems Components

Data Base

Report Writer

Graphics

Computing Facilities - Processor, Storage, I/O Devices

Communications

Human Skills:

Objectivity Communication

Clear Thinking Analytical Ability

Lateral Thinking Computer Literacy

Adaptability Tenacity


The Decision MakersThe Decision Makers

Who are ‘The Decision Makers’ ?

In the early days of decision support, the Decision Makers were a small group of high-level executives (does this sound familiar ?)

Since then however, the business intelligence industry has helped push data-driven decisions to a much wider user environment


The Decision MakersThe Decision Makers

Today, the ‘decision makers’ are business people who are closest to the point where an action needs to be taken.

This can be:– in the supply chain– when in contact with a customer (email, web-mail,

telephone, (fax ?)– at a strategic executive meeting


Business IntelligenceBusiness Intelligence

Business Intelligence addresses :

Synthesising or constructing useful knowledge from large sets of data

It involves

integration

summarisation

abstractions

ratios

trends

allocations



It addresses

comparing generalisations based on data with model-based assumptions

reconciling these when they differ

creative thinking supported by data

using data carefully

understanding how to calculate derived data

continual learning

modifying goals



The functions which support Business Intelligence are– data collection– data storage (why ?)– data translations - time, currencies– dimensional structuring (allows for extractions on a

number of bases)– access models– predictive models– model verification– knowledge sharing– resource allocation scenarios– decision implementation strategies


Decision Support Systems Decision Support Systems

Provide a quick response to SIMULATED problems (software support)

Generally LESS COSTLY than real life exercises

Variety of ‘business decision models’

- linear programming

- decision trees

- simulation

- queueing

- financial analysis DCF, NORMDIST, NPV

- forecasting / projections Which one(s)

- risk analysis best suit the

- sensitivity analysis conditions ?


Decision Support Systems SoftwareDecision Support Systems Software

• Model Building– Relationships between parameters

• What-if Incremental Assumptions– Highly useful aspects

• Backward Iteration– Establish a Target and work back - ( ? regression)

• Risk Analysis– Use probability distributions to assess outcomes

• Statistical Analysis and Management Science Models– Regression Time Series Analyses

• Financial Functions– Depreciation Methods Return on Investment



• Programmable Tasks = Rules / Procedures Known

* Clear Rules

* Rules can be built into a software program

* All required data is available

* The Decision maker is supported by software processes

* Complex situations may indicate a very deep but

‘modular’ and / or progressive structure

• Some Examples:

* Mergers, Takeovers, Off-Loadings

* Plant Expansion

* New Products

* Portfolio Management * Marketing


Decision ProcessingDecision Processing

Decision Processing

Extract/transform/load(ETL) toolsInformation templates

Business Intelligence (BI) toolsReporting/analysis templatesPackaged analytic applications

ERP and othertransaction-processingsystems

Federateddata warehouse

Web basedInformation Portal

Information flow in a decision-processing system

Oracle, SAP, People Soft SAP’s Business Information Warehouse


Application TaxonomyApplication Taxonomy

Application Segment Application Types

Financial Management Financial consolidation

Budgetting and planning

Cost and profitability analyses

Risk management

Fraud detection

Customer Relationship Customer profitability, retention,

Management (sales, cross and up selling

marketing, service) Customer segmentation, behaviour analysis

Sales force analysis

Promotion and campaign analysis

Product performance analysis



Application Segment Application Types

Supply chain performance Demand planning

management Inventory control

Distribution efficiency and

optimisation

Human resource Management Workforce planning and

optimisation

Salary planning and analysis

Employee retention

Executive Business Scorecard/key performance

performance management indicators



E- business management Promotion analysis and channel comparison

Inventory control and supplier analysis

Product and shopping analysis

Support from packaged decision-processing solutions:

SAP : Business Information Warehouse - SAP R/3 transaction processing

Oracle : Sales Analyser. Financial Analyser. Activity Based Costing. Balanced Scorecard.

Others : IBM, Information Builders, Informatica, Sybase, ...

Taxonomy means classification



• Non-Programmable Tasks

* Unstructured = No Definable Rules

* Does not permit software programs to be developed

* Cannot determine :

- Objectives

- Trade Offs

- Relevant Information

- Methods for analyses


Decision SupportDecision Support

• Some Offsets:

Managers tend to be busy and highly paid

This will normally lead to a reluctance to learn the ‘special features’ of a software package

OR to understand the problem which the software BEST addresses

• A brief and cursory understanding may lead to– lack of understanding of limitations– lack of clarity in interpretation of results



• Related Matters

Economic models invariably are developed for

‘General Cases’

Quality of Information Used

Some models have default values/options - may not be suitable for specific instances



Uncertainties - types and sources of

- effects on decision making

A few examples:– response to direct mailings– Internet home page accesses– default rates for loans– sales reports

• sales reports - doubts - are ALL sales reflected ?

- how is ‘missing’ data handled - 0 ?

- is the program 100% error free ?• Can such doubts be quantified ? Should they be ?



Data uncertainty can be : predictions

historical

Budgeting, marketing are widely analysed using spreadsheets.

Uncertaintities are handled (generally) with a single valued estimate.

Next year’s sales may include a single estimate in the budgeting exercise.

Healthcare (as in Medicare) may be based on a single value for doctors’ productivity (or hospital case-mix).



Let’s look at a company which is trying to float a new product, or increase its sales of an existing product.

5 possible promotional methods are available– radio– newspaper (local, local/country, local/interstate ?)– television advertising– direct mail– an ‘all-bells and whistles’ presence on the World Wide

Web

There is a hidden agenda - what is the Competition doing or how is it going to react ?



There could be :– no competition– low competition– medium competition– high competition– multiple competitor competition (e.g. car industry)– and what is ‘low’, ‘medium’, ‘high’ ? How are the

parameters set ?• A decision analysis tool will accommodate a probabilistic

component.• The ‘unknown’ is a spreadsheet model is the range of

likelihood of competitive promotions, and of course their effect on sales



A decision analysis tool will simulate a number of scenarios based on the specified probabilities, and will indicate the decision which will (in this case) have the best likelihood of maximising profit.

And the past ? - meaning legacy or historical data ?– Quality of data is important here– Customer code structures - any changes over 3 to 5

years– Customer name spelling ?– Incorrect replication– Regional boundary alterations ? - are we able to compare

oranges to oranges ?



• What about missing data - is it shown as zero ?• Data in the wrong field - a name in an address field ?• The number of items on an invoice = the number actually

received ?• Deliberate errors on response cards - age, income, number

of people living at an address, types of goods normally purchased etc.

• And finally, does software assume for example an even distribution of error ?


Office AutomationOffice Automation



Changes in Technology

Competitive Advantage

Business Justification

Organisational Changes

Information Systems

Decision Support

Project Evaluation

Data Planning

4GL / Windows XX

Planning Methods

Mainframe/Mini/PC

Office Automation

VideoText

Database Technology

Demands Possible Solutions



• Some Current ‘New’ Software:

Crystal INFO - Workgroup Decision Support for 5 Users

Interbase - The scalable SQL Server

Power Builder ‘For delivering fast applications anywhere’

Centura - Client Server Applications

CASE/Modelling Tools 44 products

Client/Server Application Testing 21 products

Data replication 9 products

Database Accounting 23 products

Database Application Development 88 products

Decision Support, OLAP 52 products



Also known as Personal Productivity Tools

Some Examples Spreadsheets

Word Processing / Desktop Publishing

Electronic Mail

Tele Conferencing

Electronic Funds Transfers

Electronic Document Filing (and retrieval)

Electronic Document Interchange *

Windows

User Networks

Textual Databases

and: Smart Telephones, Fax, Videotext, Electronic Bulletin Boards


Electronic Data InterchangeElectronic Data Interchange

This is the process of electronically transferring data in document which have been specially formatted

The documents are moved between businesses, and include documents such as orders, invoices, contracts, receipts, transfers, credit approvals, delivery and shipping documents.

They are normally formatted or structured documents, whereas emails are unstructured or free-form

Normally called ‘EDI’


Electronic Data InterchangeElectronic Data Interchange

Typical examples are :

– Ordering of Goods and Services ( ? Internet)– Delivery Co-Ordination– Negotiation of Prices

– e.g. Computer Aided Livestock Marketing– Stock Exchange

The documents are repetitive - meaning that they occur frequently in the business operations

There is an ANSI standard for Canada and the USA.


Electronic Document InterchangeElectronic Document Interchange

• Banking, Insurance, Superannuation,Financial Services, Production, Retail, Transport.

• Data Security : Adoption by Australia of the OECD Cryptography Policy Guidelines

Implementation phase of the SWIFT/BOLERO model

for electronic negotiable bill of lading

Introduction of Australian legislation tp

provide powers to regulate electronic documents for sea carriage of goods


EDI Electronic Document InterchangeEDI Electronic Document Interchange

– Acceptance of all major international bankcard operators of their agreement to the use of the ‘SET’ (Secure Electronic Transaction) protocol for credit card payments and collections

– The successful use of Tenet, the first intranet based fully electronic court room in the Victorian Supreme Court (a full trial without there being any paper documents presented in the court)

• However, there are delays in reforms and draft legislation to enact the privacy principles of the European Union.

• And, there are delays in some States with laws of evidence in the Evidence Act 1995.


EDI Electronic Document InterchangeEDI Electronic Document Interchange

Management Advantages

– Reduction / Elimination of Data Entry Staff

– Security (improved with the use of the Internet)

– Speed

– Accuracy

– Confirmation of Process


Hardware and Software SelectionHardware and Software Selection


Hardware/Software SelectionHardware/Software Selection



• Some Current ‘New’ Software:

Crystal INFO - Workgroup Decision Support for 5 Users

Interbase - The scalable SQL Server

Power Builder ‘For delivering fast applications anywhere’

Centura - Client Server Applications

CASE/Modelling Tools 44 products

Client/Server Application Testing 21 products

Data replication 9 products

Database Accounting 23 products

Database Application Development 88 products

Decision Support, OLAP 52 products



• Some Common Management Concerns:– Will it perform to ‘Expectations’ – Will it provide the ‘required management support’– Will it be a good investment– Does the organisation (person) have

– a real need– the appropriate environment

Prepare: Analyse, Plan, Review, Decide, Communicate

and obtain other user’s experience



System Design Stage

Develop CRITICAL ITEMS - Hardware Software Budget,

Delivery Time, Turnkey,

Performance, Uptime

ESSENTIAL ITEMS - Expansibility, Compatibility

NORMAL ITEMS - Software, Clear Statement of

deliverables, Supply of manuals,

training, vendor record

OTHER - Quantification of Hardware, Installation

Assistance, Warranty



It’s also worthwhile to do some Reliability Sampling analyses on the Permutations to develop a comfort index.

SPSS ?SPSS ?

It’s also worthwhile to do some Reliability Sampling analyses on the Permutations to develop a comfort index.

SPSS ?SPSS ?


Hardware and Software Selection

Hardware and Software Selection

Areas or Aspects of Submissions for Assessment

Hardware:

Expansion capability

Reliability

Maintenance

Software

Operating System and Upgrades

Communications Capability

Training

Security

Documents

CSE1720 Semester 1 2005 week 11 / 1 Lecture No. 11