Systems Thinking & Business Analytics Flashcards
Data, info and knowledge continuum
Data to info to knowledge to wisdom
Data
Facts and figures without any real context or meaning
Information
Data that has been made meaningful and helps someone understand something.
Knowledge
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.
Wisdom
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
Big data
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
Three characteristics that apply to Big Data
Volume, variety and velocity
Problem with Big Data
The problem with big data is it cannot be easily manipulated or processed through the use of traditional data processing software.
Problem
A situation that may cause damage to or provide opportunities for the operation of the business
First step of solving problems
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
Taking a systems thinking approach to problems
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
The following scenario is an example of a well-intentioned person failing to use systems thinking in practice
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.
System
A collection of interrelated components that function together to achieve some well-defined purpose(s)
Natural system
occurs naturally in the world (eg, respiratory system, human body, ecological system, solar system)
Designed Abstract System
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)
Engineered/Technical system
a man-made system that is physically implemented (eg, a toaster, a car)
Human activity system
systems where people come together for some purpose (eg, an accounting department, a sports club, a university). Includes business organisations
The key system characteristics
Photo 1
The purpose of a system
To learn about problem solving/identifying business opportunities
System characteristics
Inputs Outputs Components Interrelated Components Boundary Environment Interfaces Constraints Stakeholders
Inputs
whatever a system takes from its environment in order to fulfil its purpose
Outputs
whatever a system returns to its environment in order to fulfil its purpose
Component
a part, or aggregation of parts, of a system, commonly referred to as a subsystem
Interrelated components
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
Boundary
the line that distinguishes the inside from the outside of a system and so distinguishes the system from its environment
Environment
everything external to a system that interacts with the system
Interfaces
points of contact where a system meets its environment or where subsystems meet each other
Constraints
limits or conditions within which a system can accomplish its objectives
Stakeholders
person(s) or organization(s) that have a direct interest in the system
Classroom example of inputs
students needing to learn about systems thinking
Classroom example of outputs
students knowing about systems thinking
Classroom example of component
research the content, prepare lecture content, plan delivery, deliver content, assess with feedback on whether transformation achieved
Classroom example of interrelated components
cannot deliver content without research and preparation
Classroom example of boundary
this class on systems thinking within the context of the business computing course
Classroom example of environment
the business computing course in current semester
Classroom example of interfaces
interfaces with the degree, timetabling and enrolment systems
Classroom example of constraints
delivered in 1 hour in a lecture room
Classroom example of stakeholders
you, lecturer, admin, course co-ordinator, program co-ordinator
Classroom example of purpose
To learn about systems thinking
Systems thinking - nice problems
Well defined structure comprised of parts and relationships. Suitable for systematic reduction of the whole problem to its component parts.
Systems - thinking messy wicked problems
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?
Are the following examples of nice problems
Only d is a nice problem
Photo 2
What makes a problem wicked
Wherever there are people involved with different viewpoints it could potentially be a wicked problem!
Purpose of a rich picture
Concerned with defining the options for improvement. Suitable for Messy “Wicked” Problems.
Soft systems is essentially
committed to the examination of human activity.
A soft systems thinking approach
A Soft Systems Thinking approach seeks to find the most appropriate solution for the situation.
A hard systems thinking approach
A Hard Systems Thinking approach seeks to find the most efficient solution for the situation.
When dealing with messy problems system analysts often use (soft systems thinking)
tools to help them visualise complex situations – in particular situations involving many different people who each hold different views.
A key goal of soft systems thinking tools
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
Rich Picture example
Photo 3
What is a rich picture
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
Rich picture example 2
It should be people, not departments Photo 4
What are the key issues and concerns shown in photo 4
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
What tasks might the organisation in photo 4 carry out to survive
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)
IPO Charts
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.
IPO Chart example
Photo 5
Reporting tools
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
Data mining tools
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.
Knowledge management tools
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.
Example 1 of why business analytics is important
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!
Example 2 of why analytics is important
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.
Exam question 1
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Exam question 2
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