cc6052 review & revision

7/29/2019 CC6052 Review & Revision

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Revision and Review

CC6052Management Support Systems

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System concepts

MIS, DSS, ES, EIS, BI, ...

Technology concepts

Database: Data warehouse, data mart, data mining, OLAP

Other technologies:AI, ES, ANNs, fuzzy logic,

genetic algorithms, intelligent agents, game theory

Management techniques

SMART objectives, KPIs, KM, what if? analysis ...

Functional business concepts

CRM, ERP, HRM, Supply chain management, ...

Key Concepts covered in module

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Exam format

Exam is 2 hours

Choice ofany three questions from five

All questions carry equal marks

No compulsory question

Case study is provided (Officionado Ltd)

Some questions will relate directly to case study

use case study for examples apply your knowledge in context of the case study

Similar past papers Management Support Systems

Old codes: BS3002, CC30013


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Summary

Management Support Systems key issues

Certainty, risk and uncertainty

Database, data mart, data warehouse

Data, information and knowledge

Data mining

Data transformation

Definitions: OLAP, OLTP

Executive dashboard

Expert Systems and Intelligent SystemsStrategic analysis SWOT and Balanced Scorecard

Types and sources of data

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Summary


Certainty, risk and uncertaintyDatabase, data mart, data warehouse


Data mining

Data transformation


Executive dashboard



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Decisions: categories

Decisions can be made in the face of:

Uncertainty

Several possible outcomes for each course of action

Decision-makerdoes not know(and cannot estimate) probabilities

Risk

Decision-maker must consider several possible outcomes for each

course of action

Probabilitiesof given outcomes are known or can be estimated

Certainty

Assumes full and complete knowledge is available

Decision-makerknows the outcomeof each course of action


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Summary




Data, information and knowledgeData mining

Data transformation


Executive dashboard



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Typical (simplified) scenario

Operational

users

TPS or OLTP * TPS databases

Tactical

management

MIS

Data mart

Strategic

management

EIS

Data

warehouse

External data?

*TP

S=TransactionProcessingSystems

*OL

TP=OnlineTransactionProcessing


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Data marts

More than a database

Similar to a data warehouse, but

fordepartmentalrather than organisationaluse

specifically designed for the information needs of a

particular group rather than just based on data that happens to exist


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Data warehouses

Accessed by BI applications

retrieve data for analysis using OLAP

Contain multi-dimensional data,

e.g. sales data by

customer(and customer groupings)

product(and product categories)

time period

e.g. month, quarter, year

geographic region

e.g. area of town, district, country, world


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Data warehouses

Subject-oriented

customer, product, ...

Integrated

collected from diverse sources, internal and external

Time variant

accurate at some frozen point in time,

not time of access, not right now

Non-volatile static, not updated in DW, transferred from volatile TPS periodically

in support of managements decision-making process

for Management Support Systems


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Summary





Data transformation


Executive dashboard




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Data, information or knowledge?

Data, information and knowledge...

Names of areas and map references would be

considered data

Details of distances and direction between areaswould be information

Details of routes constitutes knowledge


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Summary





Data miningData transformation


Executive dashboard



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Data mining

Used to identify

in the data within a data warehouse

Has applications in Customer Relationship Management(CRM) analysis of loyalty card data

analysis of web-site activity 15


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Data mining

Identifying patterns, trends or correlations in the data...

Association

one event is connectedto another event

Sequenceor path analysis

one event leadsto a later event

Classification

new patterns that may lead to new ways of organisingthe data

Clustering

gathering & documenting groups offacts not previously known

Forecasting

discovering patterns in data leading to reasonable predictions


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MIS

Whoare in the top 20% of our customers?

EIS / OLAP

Who are the top 20% customers for a particular productrange and/or

in a particular geographic regionand/or

in a particular timeperiod?

Data mining

What are the characteristicsof our top 20% of customers?

MIS, EIS/OLAP and Data Mining


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Summary





Data mining

Data transformationDefinitions: OLAP, OLTP

Executive dashboard

Expert Systems and Intelligent Systems

Strategic analysis SWOT and Balanced Scorecard


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Data and information: processes

Data is processedortransformedto produce information

Examples ofdata processes: classification

rearranging / sorting

aggregating performing calculations

selection

exceptions

presentation (graph / table / chart / diagram)

Information produced used to support decision-making(Chaffey, 2003)


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Summary





Data mining

Data transformation

Definitions: OLAP, OLTPExecutive dashboard




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On Line Analytical Processing (OLAP)

Functionality for real-time analysis of multi-dimensional data

Term is used to cover

end-user software

or

or

both the software and the data

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OLAP allows users to navigate through multi-dimensional dat

(a hypercube)

whichdimensionsto view?

time, area, sales, products, customers, income, profit...

how to aggregatethe data?

profit per customer, sales per employee, trends over time...

slice and dice

data mining...


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OLAP analysing data in visual form, different dimensions


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On Line Transaction Processing (OLTP)

Updating database

When an item is:

ordered by a customer sold reduce number in stock

delivered new stock available

on order waiting for delivery

reduced lower price to encourage sale

returned not wanted by customer

faulty damaged or not working

missing unable to locate item


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Summary







Executive dashboardExpert Systems and Intelligent Systems



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Executive Information Systems (EIS)

Executive Information Systems

Characteristics

easy-to-use graphical user interface, e.g. an executive dashboard for casual users of the system want answers, not SQL skills! provide reporting and analysis (OLAP*) features enable drill down from summary information to detail data

managers want to make strategic decisions

based on an organisation-wide repository of information,

e.g. a data warehouse (with data from multiple TPS sources

used by senior management: select, retrieve & manage informationto support the achievementof an organisation's business objectives

* OLAP = Online analytical processing - do not confuse with OLTP!26


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graph

pie chart

Map with hot spots of activity

simulation,animation,picture dial

combined representations

Executive Information Systems (EIS)Executive dashboard tools

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Unlimited Drill Downs

Drill Downs both Vertically and Horizontally

Custom Views

Track Projects and Milestones with Email Alerts

Trending of Data

Create "if then" expressions for detailed analytics Advanced Charting and Graphing

Detailed Reports

Identify, track, trend, and correct problems

Identify operational efficiencies

Proactively identify and apply corrective measures

How could Officionado managers make use of such a system...?clients...orders...products...product groups...suppliers...staff best clients: corporate/private

best products: which sell well, which sell best within product group

sales staff: most sales/most revenue

suppliers: suppliers of most popular products

areas: where there are most sales

Executive Information Systems (EIS)

Typical features offered in commercial products:

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Summary







Executive dashboard



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Objective: transfer expertise from expert to ES to non-expert (user)

Involves:

Knowledge acquisition (knowledge elicitation from a person) Knowledge representation

Knowledge inferencing

Knowledge transfer to user

Turban(2001)

Expert Knowledgeengineer

Expertsystem

User

Development(including knowledge acquisition)

Consultation

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Transferring expertise


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Structured interviews

Expert is interviewed

identifies important itemsin the domain

identifies associated attributes

Repertory Grid Analysis create a scale of characteristics(opposites)

place items on scale

solutions are placed on grid(table)

Triads

Groups of three items are classified

why two are alike, and the third different

combine in many different ways 31

Gathering expertise


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Triads example

Ed

Miliband

Ronald

Reagan

Margaret

Thatcher

Ronald

Reagan

Margaret

Thatcher

Ed

Miliband

Ronald

ReaganEd

Miliband

Margaret

Thatcher

male

female

living

deceased

right-wing

left-wing


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Knowledge identified, stored and represented

Semantic networks

Association lists (alists)

Search trees

depth-first search

breadth-first search

Frames

Facts

Rules

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Knowledge representation


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Production rules

format:

pattern action

typically in the form ofifthen

rules in prolog:

predicate is true if components satisfied

sibling(X,Y) :- parents(X, M, F), parents(Y, M, F).

X is a sibling of Y if

X has motherM and fatherFand

Y has mother M and fatherF

Check whether person X is their own sibling! 34

Rules


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Intelligent agents

Intelligent agents are programs that... work in the background without direct human intervention...

perform specific, repetitive, and predictable tasks...

for an individual user, business process, or software application...

with some degree of independence

Agents use in-built/learned knowledge to

accomplish tasks/make decisions for the user

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Intelligent agents - levels

Level 0 - e.g. web browsers

agents retrieve documents for userunder direct orderse.g. user specifies URL

Level 1 - search engines

agents provide a user-initiatedsearch facility

Level 2 - software agents

o maintain users profiles

o monitor Internet information

o notify userswhen relevant information is found

Level 3 - learningortruly intelligent agents

o have a learning and deductive component of user profiles to help a user

who cannot formalise a query or target for a search36


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Intelligent agents - applications

Intelligent agents can be programmed to make decisions based on user's

personal preferencese.g. delete junk e-mail schedule appointments

travel over interconnected networks to find the cheapest airfare


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An agent is like a personal digital assistant collaborating

with the user in the same work environment

can help the user byo performing taskson the user's behalf

o trainingorteachingthe user

o hiding the complexityof difficult tasks

o helping the user collaboratewith other users

o monitoringevents and procedures

Intelligent agents - applications


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Summary

Management Support Systems

key issues

Certainty, risk and uncertaintyDatabase, data mart, data warehouse




Executive dashboard


Strategic analysis SWOT and Balanced ScorecardTypes and sources of data

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SWOT analysis

Involves a detailed and exhaustive assessment of the

strengthsand weaknessesof the business

and the opportunitiesand threats

presented by its product markets and other environments suchas suppliers and technology developers

(Pearson, 1999)

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SWOT analysis

Opportunities A B

Threats C D

Externalfactors

Strengths Weaknesses

Internal factors

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Balanced Scorecard

Traditional performance measurement basedmainly on financial measures

Balanced scorecard designed to translate

overall mission and business strategyintospecific, quantifiable goals

Usually divided into 4 key areas: financial customer

internal business process

learning and growth 42


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Summary





Data transformation


Executive dashboard



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Data and information: types, sources

Types of data: qualitative quantitative

Sources of data:

internal external private

Information:

data processed for a purpose reduces uncertainty about a situation

Managers need information tosupport their decision-making

i.e. any management decisionwill have associated

information needs

(Chaffey, 2003)

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Summary


Certainty, risk and uncertainty Database, data mart, data warehouse

Data, information and knowledge Data mining Data transformation Definitions: OLAP, OLTP Executive dashboard

Expert Systems and Intelligent Systems Strategic analysis SWOT and Balanced Scorecard Types and sources of data

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Good luck in all your examinations!

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cc6052 review & revision

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