5.9 Management Information Systems (HL) Flashcards
5.9.1 Data Analytics (A01)
Define the term ‘Data Analytics’
Specific who does this and how it is captured.
Name and explain the four main types of ‘Data Analytics’
State a Top Tip
LINKS TO ‘DESCRIPTIVE STATISTICS’
Definition:
The management process of examining and scrutinising raw data to find meaningful trends and patterns to support business decision-making.
Data analysts are hired to do this. Data is captured electronically with computer management information systems to actually analyse the data.
Data analysts use four main types of data analytics:
1. Descriptive data analytics - What happened (what does the data reveal)?
2. Diagnostic data analytics - Why did it happen?
3. Predictive data analytics- What is likely to happen in the future?
4. Prescriptive data analytics - What should be done, i.e., what is the best course of action?
TOP TIP:
Do not assume that having more data always means that management decision-making is improved. ‘DATA OVERLOAD’ can occur, causing inefficiencies and delays in decision-making.
5.9.2 Database (A01)
People often use the terms “data” and “information” interchangeably, but they actually mean different things.
Define the term ‘Data’
State the two main types of data
Define the term ‘Information’
Outline the ‘Differences Between Information and Data’
Define the term ‘Database’
DATA
Definition:
raw facts or statistics from which information is generated. It can come in the form of numbers, graphs etc. It is a raw form of knowledge or information, so does not carry any real significance or purpose on its own.
There are two main types of data:
1. Quantitative data - in numerical form
2. Qualitative data - in descriptive form
Information definition:
The organization and interpretation of facts or statistics from the given data
DIFFERENCES BETWEEN INFORMATION AND DATA:
DATA:
1. Collection of facts and statistics
2. Raw and unorganized
3. Abstract and meaningless
4. Insufficient for decision-making
INFORMATION:
1. Puts facts and statistics into context
2. Processed and organized
3. Adds substance and meaning
4. Decisions are based on information
DATABASE:
Definition:
An organized collection of data stored and retrieved electronically using a local computer or networked computer server.
INFORMATION NOT NEEDED:
Advantages:
1. easily searched and retrieved data
2. Operational efficiency
Disadvantages:
1. Overwhelming
2. Prone to cybercrime
5.3 Cybersecurity and cybercrime
Define the term ‘CyberCrime’
What is happening with ‘CyberCrime’ as time passes?
Define the term ‘Cybersecurity’
State two ADVANTAGES and DISADVANTAGES
CYBERCRIME
Definition:
Any form of illegal activity carried out using electronic methods to deliberately and maliciously attack computer hardware or software. Most cybercrime is committed by hackers (or cybercriminals).
The cost of cybercrime to organisations is growing due to the increase in the reliance on the Internet.
CYBERSECURITY
Definition:
A firm’s policies, processes, and procedures used to safeguard its computer systems and networks from unwarranted attacks, such as information disclosure, data theft, or physical damage.
NOT NEEDED BECAUSE A01!
ADVANTAGES:
1. Data Protection - safeguards sensitive data
2. Business Continuity - protects against disruptions
DISADVANTAGES:
1. Cost of Implementation - cybersecurity technology and training
2. Resistance to change - employees may resist adopting new security protocols.
5.9.4 Critical Infrastructures (A02)
Define the term ‘Critical Infrastructures’
State the three different features of ‘Critical Infrastructure’
Define the term ‘Artificial Neutral Networks’
State an example
Define the term ‘Data Centres’
State an example
Define the term ‘Cloud Computing’
State an example
CRITICAL INFRASTRUCTURES
Definition:
The crucial computer systems, structures, networks, and facilities required for the effective functioning of an organization in the modern and digital corporate world.
They consist of both physical infrastructures (ANN and data centres as well as non-physical infrastructures (cloud computing).
There are three different features of ‘Critical Inrastructure’:
1. Artificial Neutral Networks (ANN)
2. Data Centres
3. Cloud Computing
- ARTIFICIAL NEUTRAL NETWORKS (ANN)
Definition:
advanced computing systems that are designed to simulate how the human brain processes and analyses data and information. It relies on the use of learning algorithms to do so.
Examples:
Chatbots - maintain online discussion with a customer, as if it were a real human.
- DATA CENTRES
Definition:
the physical facilities or the locations of computer systems with networks and structures that support organisations in accommodating their telecommunications and data storage systems.
Services provided by data centres include:
AI, Big Data, Email and firesharing
- CLOUD COMPUTING (otherwise referred as cloud services)
Definition:
a virtual, computer generated online space that enables businesses to store, organise, manage, process, and retrieve data in safe and efficient ways. It doesn’t require any external storage equipment.
There are three categories (or types) of cloud computing:
1. Private Cloud - managed by the firm
2. Public Cloud - managed by an external cloud service provider
3. Hybrid Cloud - combination of a public and private cloud
5.9.5 Virtual Reality (VR) (A02)
Define the term ‘Virtual Reality’
State two ADVANTAGES and DISADVANTAGES of Virtual Reality
VIRTUAL REALITY
Definition:
An artificial, computer-generated environment or world accessible to the consumer in a seemingly real-world way, such as interactive simulations using highly sophisticated computer equipment. Can be used for training by relating situations in a safer way.
ADVANTAGES (of virtual reality in the workplace):
1. Reduce Wastage and accidents in the workplace -
safer environment for employees to train
2. Highly flexible - can be used for a very broad range of scenarios
3. Fewer distractions during training- in real-world training is often disrupted by interactions/distractions
DISADVANTAGES:
1. Challenging to keep up with technological advances - equipment becomes obsolete quickly
2. Expensive -investment into VR hardware and software, no guarantee investment will be successful
3. Motion sickness from employees
5.9.6 The internet of things
Define the term ‘The Internet of Things’ and what it is used for in a general sense
Specify ways in which a firm uses ‘The Internet of Things’
State examples of ‘The Internet of Things’
THE INTERNET OF THINGS
Definition:
Any Internet-enabled device that enables people to store, share, and transfer data with other electronic devices that can connect to the Internet by using embedded sensors. The data are used to detect patterns, make recommendations, and identify possible problems before they occur.
Businesses use it to:
1. Track customer spending habits
2. Enhance supply chains
3. Improve stock control
Examples:
Amazon’s Echo, Apple’s Smartwatch, farmers use the IoT technologies to primove agricultural output and pest control (PAPER 1 CASE STUDY), satellites
5.9.7 Artificial Intelligence (A03)
Define the term ‘Artificial Intelligence (AI)’
State some examples of ‘Artificial Intelligence (AI)’
State two ADVANTAGES and DISADVANTAGES of businesses using ‘Artificial Intelligence’
ARTIFICIAL INTELLIGENCE (AI)
Definition:
Area of computer science/The theory and development of computer systems able to perform tasks that normally require human intelligence
AI enables computers and IoT devices (the Internet of things) to mimic human behaviour and actions
Examples:
1. Online search engines and social media platforms
2. Facial and voice recognition systems to access online banking and on smart devices
3. Satellite navigation systems
ADVANTAGES:
1. Increased Customer Knowledge - allows for processing of large volumes of data faster
2. Efficiency - no need to rest (24/7), handle tasks at a volume and velocity humans can’t possibly match
3. Unbiased decisions
DISADVANTAGES:
1. Mass Unemployment - bad for the economy and not ethical (reduced corporate image)
2. Lack of Emotion/Human Care - lacks the humanity and emotion to operate ethically
3. Make Humans Lazy - reduce the skilled availability of human resources in the future
EXTRA INFORMATION
Machine Learning: A dimension of artificial intelligence, this refers to the use of computer systems, algorithms, and statistical models to enable electronic devices to memorize and adapt on their own without following direct instructions.
5.9.8 Big data (A02)
Define the term ‘Big Data’
State and briefly explain the five characteristics of ‘Big Data’
Provide an Example
State two ADVANTAGES and DISADVANTAGES of using ‘Big Data’
BIG DATA
Definition:
The access to extensive amounts of unprocessed (raw) and processed (structured) data from a broad range of sources.
The data are often complex, due to the huge volume available, so sophisticated computer systems are used to capture, process, and analyze the data
There are five key characteristics of big data, referred to as the 5Vs
1. Volume - large amount of data generated
2. Variety - the diversity or different types of data
3. Velocity - the speed at which data are generated and stored
4. Veracity - the extent to which the data are accurate
5. Value - the extent to which the data are useful for supporting problem-solving and improving decision-making
Example:
Airline companies use big data to determine different prices to charge passengers on each day of the year, using dynamic pricing.
ADVANTAGES:
1. Endless Volume of Information
2. Improve Strategic Decision Making
DISADVANTAGES:
1. Cybersecurity Risks - privacy and security concerns
2. Hardware Needs - expensive,no guarantee of financial return
5.9.9 Customer Loyalty Programmes
To refresh your memory, review the definition for ‘Customer Loyalty’
Define the term ‘Customer Loyalty Programmes’
State two ADVANTAGES and DISADVANTAGES of ‘Customer Loyalty Programmes’
IMPORTANT TO REMEMBER:
Customer Loyalty Definition:
The extent to which customers consistently repurchase products from the same business
CUSTOMER LOYALTY PROGRAMME
Definition:
Marketing strategies designed to retain customers by using a rewards programme that give loyal customers direct benefits, such as reward points that can be redeemed for purchases at discounted prices, coupons etc.
This can be enhanced by MIS to gather and process data about their customers e.g purchase history
ADVANTAGES:
1. Customer Retention BECAUSE they reward customers for repeat purchases
2. Cost efficiency - It can be significantly cheaper to retain happy customers than search for new customers.
3. New Revenue stream - by charging upfront membership fees
DISADVANTAGE:
1. Time - to develop and nurture
2. Competition - competitors will also offer their own schemes that reward devoted customers
3. Excessive Expenditure - can encourage customers to overspend and even raise the level of consumer debt
5.9.10 Digital Taylorism
Define the term ‘Digital Taylorism’
Outline where this came from and what is the difference between ‘Digital Taylorism’ and ‘Scientific Management Theory’
Give examples of what ‘Digital Taylorism’ entails
State two ADVANTAGES and DISADVANTAGES of ‘Digital Taylorism’
DIGITAL TAYLORISM
Definition:
Management approach that relies on management information systems to improve productivity by managing employees and the tasks they perform in the most systematic and methodical ways. This involves the use of digital technologies to streamline and automate tasks so as to improve efficiency and productivity
The approach comes from the works of Frederick .W. Taylor.
The difference between scientific management and digital Taylorism is that the former required managers to observe the work of employees and managers, whereas the latter relies on computerised systems to do so. For example, a business can use digital technologies to track:
- How long an employee spends on a particular website
- What employees search for on their computers
- The contents of emails sent by employees
ADVANTAGES:
1. Precision and Accuracy - minimising human errors and inconsistencies in production or service delivery.
2. Promotes Standardisation - ensuring tasks are performed consistenly and according to predefined standards.
3. Data driven (scientific) decision making
DISADVANTAGES:
1. Resistance of Change - concerns about job security, being micromanaged etc.
2. Monotony - due to division and automation of tasks so reduce job motivation
3. Limited scope of creativity
5.9.11 DATA MINING
Define the term ‘Data Mining’
State two ADVANTAGES and DISADVANTAGES
DATA MINING
Definition:
The management process of using data for predictive analysis and forecasting purposes. It is the use of management information systems to find trends, patterns, and correlations from large data sets, and using the findings to make informed predictions about future situations, rather than base decisions based on intuition
Data mining relies on other aspects of MIS, such as:
1. Databases
2. Data Analytics
3. Big Data
ADVANTAGES:
1. Help manager and decision makers to predict future situations - less vulnerable
2. Effective use of data allows businesses to understand their customers better, which helps to improve customer relations
3.Informed decision making = increase sales reveneu
DISADVANTAGES:
1. Privacy issues - due to increase amount of data about private individuals on platforms.
2. Security Issues - surrounding hackers gaining access to data of customers
3. Highly expensive - investment into advanced technologies and hiring specialists.
3.
5.9.12 Benefits, risks, and ethical implications of MIS (AO3)
Define the terms:
1. Management Information System
2. Technological Innovation
These two things have BENEFITS, RISKS, and ETHICAL CONSIDERATIONS on decision-making and stakeholders.
SPECIFY TWO-THREE FOR EACH
MANAGEMENT INFORMATION SYSTEMS (MIS)
Definition:
the collective term for the advanced computer technologies and technological innovations that influence business decision-making and stakeholders of a business.
TECHNOLOGICAL INNOVATION:
Definition:
The partial or full replacement of an existing technology by one that improves a firm’s productivity, its product quality, and competitiveness in the market
These two things have BENEFITS, RISKS, and ETHICAL CONSIDERATIONS on decision-making and stakeholders.
BENEFITS:
1. Improved decision making-
gathering of data on consumer behaviour etc
2. Better Operational Efficiency - streamline processes and reduce costs
3. Enhanced competitive advantages - insights into their competitors
RISKS:
1. Cybercrime - sensitive information, data theft etc
2. Set-up and maintenance cost - advanced technologies and training for staff
3. Regulatory compliance - legal and regulatory risks
ETHICAL CONSIDERATIONS:
1. Lack of Human Touch - rely on automated processes = absence of emotions and empathy (in terms of policies)
2. Data Manipulation - miSuse data to influence a particular decision or outcome, unethical because it is intended to mislead.
