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Business Computing > Systems Thinking & Business Analytics > Flashcards

Systems Thinking & Business Analytics Flashcards

1
Q

Data, info and knowledge continuum

A

Data to info to knowledge to wisdom

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2
Q

Data

A

Facts and figures without any real context or meaning

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3
Q

Information

A

Data that has been made meaningful and helps someone understand something.

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4
Q

Knowledge

A

Information that has been incorporated into someone’s view of the world. typically defined with reference to information. information having been processed, organised or structured in some way, or else as being applied or put into action.

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5
Q

Wisdom

A

ability to increase effectiveness and add value, which requires judgment. The ethical and aesthetic values are inherent to the actor and are unique and personal

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6
Q

Big data

A

Big Data applies to data that can’t be processed or analysed using traditional processes or tools.…organisations today have access to a wealth of data,… don’t know how to get value out of it because it is sitting in its most raw form or in a semi-structured orunstructured format

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7
Q

Three characteristics that apply to Big Data

A

Volume, variety and velocity

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8
Q

Problem with Big Data

A

The problem with big data is it cannot be easily manipulated or processed through the use of traditional data processing software.

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9
Q

Problem

A

A situation that may cause damage to or provide opportunities for the operation of the business

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10
Q

First step of solving problems

A

To solve a problem, you must first identify the cause. Symptom/Effect is a condition produced by the problem. Cause is the situation, often obscured by one/ more symptoms/effects, that is generating those symptoms

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11
Q

Taking a systems thinking approach to problems

A

Instead of breaking a situation into little pieces, take a “connected view of an organisation” Wholes - totality of persons’ lives, groups, organisations, communities. Nothing exists by itself. Take a broad view of the situation. Look at the situation from multiple perspectives

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12
Q

The following scenario is an example of a well-intentioned person failing to use systems thinking in practice

A

A physician prescribed a diet for a diabetic patient without regard for her limited income, or for her husband’s reluctance and intellectual inability to comprehend his wife’s condition or needs.

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13
Q

System

A

A collection of interrelated components that function together to achieve some well-defined purpose(s)

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14
Q

Natural system

A

occurs naturally in the world (eg, respiratory system, human body, ecological system, solar system)

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15
Q

Designed Abstract System

A

constructed by human’s, but not physically implemented (eg, the logic of a management information system, a spoken or computer language, the laws of mathematics, a religious belief system)

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16
Q

Engineered/Technical system

A

a man-made system that is physically implemented (eg, a toaster, a car)

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17
Q

Human activity system

A

systems where people come together for some purpose (eg, an accounting department, a sports club, a university). Includes business organisations

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18
Q

The key system characteristics

A

Photo 1

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19
Q

The purpose of a system

A

To learn about problem solving/identifying business opportunities

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20
Q

System characteristics

A 
Inputs
Outputs
Components
Interrelated Components
Boundary
Environment
Interfaces
Constraints
Stakeholders
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21
Q

Inputs

A

whatever a system takes from its environment in order to fulfil its purpose

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22
Q

Outputs

A

whatever a system returns to its environment in order to fulfil its purpose

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23
Q

Component

A

a part, or aggregation of parts, of a system, commonly referred to as a subsystem

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24
Q

Interrelated components

A

the dependency of one subsystem on one or more other subsystems. Subsystems are related and usually interact with each other in order to achieve their pre-declared objectives, within their environment

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25
Q

Boundary

A

the line that distinguishes the inside from the outside of a system and so distinguishes the system from its environment

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26
Q

Environment

A

everything external to a system that interacts with the system

27
Q

Interfaces

A

points of contact where a system meets its environment or where subsystems meet each other

28
Q

Constraints

A

limits or conditions within which a system can accomplish its objectives

29
Q

Stakeholders

A

person(s) or organization(s) that have a direct interest in the system

30
Q

Classroom example of inputs

A

students needing to learn about systems thinking

31
Q

Classroom example of outputs

A

students knowing about systems thinking

32
Q

Classroom example of component

A

research the content, prepare lecture content, plan delivery, deliver content, assess with feedback on whether transformation achieved

33
Q

Classroom example of interrelated components

A

cannot deliver content without research and preparation

34
Q

Classroom example of boundary

A

this class on systems thinking within the context of the business computing course

35
Q

Classroom example of environment

A

the business computing course in current semester

36
Q

Classroom example of interfaces

A

interfaces with the degree, timetabling and enrolment systems

37
Q

Classroom example of constraints

A

delivered in 1 hour in a lecture room

38
Q

Classroom example of stakeholders

A

you, lecturer, admin, course co-ordinator, program co-ordinator

39
Q

Classroom example of purpose

A

To learn about systems thinking

40
Q

Systems thinking - nice problems

A

Well defined structure comprised of parts and relationships. Suitable for systematic reduction of the whole problem to its component parts.

41
Q

Systems - thinking messy wicked problems

A

Real-world problems are usually messy, ill-structured. The actions necessary to attain goal(s) are not obvious. Several people involved with different viewpoints - whose objectives should be addressed? The customer? The salesperson? The manager?

42
Q

Are the following examples of nice problems

A

Only d is a nice problem

Photo 2

43
Q

What makes a problem wicked

A

Wherever there are people involved with different viewpoints it could potentially be a wicked problem!

44
Q

Purpose of a rich picture

A

Concerned with defining the options for improvement. Suitable for Messy “Wicked” Problems.

45
Q

Soft systems is essentially

A

committed to the examination of human activity.

46
Q

A soft systems thinking approach

A

A Soft Systems Thinking approach seeks to find the most appropriate solution for the situation.

47
Q

A hard systems thinking approach

A

A Hard Systems Thinking approach seeks to find the most efficient solution for the situation.

48
Q

When dealing with messy problems system analysts often use (soft systems thinking)

A

tools to help them visualise complex situations – in particular situations involving many different people who each hold different views.

49
Q

A key goal of soft systems thinking tools

A

is to achieve a representation of the problematic situation in a way which is as neutral as possible (i.e. an analyst does not want to jump to conclusions about what the problem is!!) This is achieved by building a rich picture

50
Q

Rich Picture example

A

Photo 3

51
Q

What is a rich picture

A

Technique used in Soft Systems Methodology (SSM) (but can be used elsewhere). A pictorial caricature of what the organisation (or group) is ‘about’. Should be self-explanatory and easy to understand. Should identify the elements of structure, process, climate, and issues in the situation

52
Q

Rich picture example 2

A

It should be people, not departments Photo 4

53
Q

What are the key issues and concerns shown in photo 4

A

Unable to quickly analyse sales. Unable to determine the commission earned by the sale representatives. Cannot analyse the product data to determine appropriate changes to the product mix. Need to determine which products and areas require more focus by the sale representatives

54
Q

What tasks might the organisation in photo 4 carry out to survive

A

Develop a process and a tool to analyse both the level and the type of sales, which can be used to produce reports as required. Such reports will aid in the performance management of the sales representatives (might possibly use a spreadsheet to prototype the tool)

55
Q

IPO Charts

A

An IPO chart records the input, processing, and output of a process, or program module. It is commonly used when designing spreadsheet formulas, calculated fields in databases, and designing algorithms in programming.

56
Q

IPO Chart example

A

Photo 5

57
Q

Reporting tools

A

These are information systems that collect data from a variety of sources, process that data, and format it into reports to business users. The processing that is applied is typically straightforward – sorting, grouping, carrying out simple arithmetic operations such as generating totals, identifying max and min values, and calculating averages. Reporting tools generate intelligence related to how the business has historically functioned, and how it is functioning at the present time. Typical of such tools are the primary functions of the Microsoft Excel spreadsheet application, about which more will be said in later chapters

58
Q

Data mining tools

A

These are information systems that process data using statistical techniques, often techniques that are mathematically complex based on possible models of the business. These tools search the data for patterns and relationships among the data. By so doing, these tools make predictions. information systems often play a key role in assisting with the process of strategic planning and problem-solving.

59
Q

Knowledge management tools

A

These are computer systems that are used to store employee knowledge, with a view to making that knowledge available widely to employees, customers, vendors, auditors etc., so supporting their decision-making. Knowledge management tools differ from reporting and data-mining tools in that the source of their data is human knowledge, rather than operational facts and figures. FAQS, search engines, web portals.

60
Q

Example 1 of why business analytics is important

A

Netflix has changed the movie rental industry using business analytics! Netflix collects extensive data using surveys, web site user testing, and brand-awareness studies. When a new customer connects they are prompted to enter genre preferences and rate a selection of movies. The Netflix movie inventory is tagged with various attributes. Customer ratings are compared with these attributes and are also matched to other people who have similar viewing histories. The result – Netflix can predict movies that each customer is likely to enjoy, and so can create individual customer recommendations. Netflix knows what movies you will like before you and your friends do!

61
Q

Example 2 of why analytics is important

A

Predictive policing refers to the application of analytical, predictive techniques in law enforcement to identify potential criminal activity. Predictive policing includes: methods for predicting crimes, methods for predicting offenders, methods for predicting perpetrators’ identities, and methods for predicting victims of crime. Predictive policing uses data on the times, locations and nature of past crimes, to provide advice to police management concerning where, and at what times, police patrols should patrol, or maintain a presence, so making the best use of resources and/or having the greatest chance of deterring or preventing future crimes.

62
Q

Exam question 1

A

Photos 1 - 3 of computing exam questions

63
Q

Exam question 2

A

Photos 4-5

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