Business 5.9 Flashcards
What is a database
computerised system that makes it easy to store, search and select raw information that can be synthesised. The two types are qualitative (employee residential addresses) and quantitative (costs, prices, etc).
What is Cybersecurity
the practice of protecting systems, networks, and programs from digital attacks.
What is Cybercrime
refers to any illegal activity carried out using computers or the Internet by deliberately and maliciously targeting computers, computer networks or networked devices. This can be carried out by individuals or organisations, usually done for financial reasons (profit), but in some cases can be caused by political or personal motives.
What is Critical infrastructure
refers to the essential and interrelated physical structures and facilities needed for the effective functioning of a business.
What are Artificial neural networks (ANN)
form of intelligent machine-learning algorithm that simulate the human brain
e.g. (→ Google uses it make its ‘watch next’ recommendations for YouTube videos.
→ E-commerce, chat bots, etc.)
What are data centres
networks of centres that store, process, and distribute data
What is cloud computing
data centres on the internet instead of a physical place.
What is virtual reality
is the use of computer technologies to create a simulated 3D experience.
Uses:
Uses of virtual reality
- Marketing: Innovative products that are designed to engage with their target markets.→ IKEA, customers can virtually place furnitures in their homes.
- Operations management: Model product prototypes using simulations with VR software, minimise errors in R&D stages, help adapt designs as needed.
- Human resource management: Train employees more effectively.
Limitation of VR
- Can be expensive for businesses to use. However, costs are coming down over time.
- Clunkiness of VR headsets may be awkward user experience, truly immersive experiences has not yet fully realised yet.
- Ethical, security-related and legal issues.
What is Internet of things
network of devices that can collect and process data
Using mobile phones as sensors to collect and share data from our vehicles via applications like Google Maps or Waze is an example of using IoT. It informs about the traffic conditions of the different routes, estimated arrival time, and the distance from the destination while contributing to traffic monitoring.
What is AI
computer systems that can perform functions traditionally handled by humans
it is made up off several ANN’s put into one big thing (AI)
Commerce: use of chatbots, customer support
Transportation: self-driving vehicles
What is big data
Extremely large data sets that are analysed to reveal trends and patterns in consumers’ behaviour
Example of big data use
Quality management: business can analyse data about consumer preferences and they can use this data to improve quality of product make sure qualty standards is in line with consumers needs and wants
Location decision: big data about suppliers location and delivery times can help to make better location decisions
BEA: analysis consumers consumers spending patterns, income levels, and levels of originations output can help to determine the bets price price, target price
analyzing demand fluctuations an predicting different kid of disturbances in supplies of raw materials can hep with production planning
analysing past data about emergencies can help with contingency planning
analyzing past data and making sure that past mistakes are not repeated again can help to minimize wastage of resources in R&D
What are loyalty programmes
measures taken to encourage customers to make repeat purchases
e.g. airline miles, banking app cashbacks, reward points
advantages of loyalty programmes
Increased customer retention
Low cost (compared to attracting new customers)
Obtaining more data from customers
Word of mouth promotion
disadvantages of loyalty programmes
having to deal with big data (dealing with servers, people and experts) its not free and not cheap, the more data colelcted th emore expensive it will be
competition with other loyalty programmes from competitors
any forms of discounts leads to reduced profits
What is digital taylorism
Digital Taylorism refers to the use of management information systems (MIS) to monitor the behaviour and performance of employees
Advantage of digital taylorism
Efficiency - Digital Taylorism can significantly improve efficiency in the production of goods and improved service processes.
Cost savings - It can lead to cost savings in the long term by automating repetitive tasks, reducing the need for extensive manual labour, and minimizing errors in production processes.
Precision and accuracy - Automation through digital technologies ensures precision and accuracy in tasks, minimizing human errors and inconsistencies in production or service delivery.
Standardization - Digital Taylorism promotes standardization of work processes, ensuring that tasks are performed consistently and according to predefined standards.
Data-driven (scientific) decision making - The use of digital technologies allows for the collection and analysis of large amounts of data, enabling firms to make informed decisions and identify areas for improvement.
Productivity gains - Automation of routine tasks can result in increased overall capital productivity, as digital systems and MIS can work continuously without the need for rest breaks.
Disadvantage of digital taylorism
Monotony - The division and automation of tasks can cause monotony so reduce job satisfaction, resulting in lower productivity and higher labour turnover.
Skills erosion - The focus and reliance on automating tasks can lead to less emphasis on developing diverse skills among workers, potentially eroding the overall expertise and skills set of the workforce.
Resistance to change - Workers may resist the implementation of digital Taylorism due to concerns about job security, loss of control over tasks, being micromanaged, and fear of being replaced by machines.
Limited scope for creativity - Overemphasis on automation and standardization may stifle creativity and innovation as workers may have limited opportunities to contribute ideas or suggestions.
Depersonalization - The reduction of human involvement in tasks and decisions may lead to a depersonalized work environment, affecting the quality of customer service and employee relationships.
Ethical concerns - The use of digital Taylorism raises ethical concerns related to job displacement, unequal distribution of power, and the potential to exploit people in the workplace.
Examples of digital taylorism
CCTV cameras: ca nhelp monitor what employees are doign at work, see if they are involved what they should not be involde it
Screen monitoring, company laptop, the company can see when you accessed and what you did on laptop
Clock-in and clock out can see when employees have entered work and left workplace
Recording voice calls, this is use of data to improve performance
email monitoring
what is data mining
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 predictions about future situations. Hence, it is sometimes referred to as knowledge discovery in data (KDD).
Data mining relies on other aspects of management information systems (MIS), such as databases, data analytics, big data, and machine learning to discover patterns and relationships (correlations) in these large data sets so as to inform business decision making. Data mining enables managers to make sense of past trends in order to make informed predictions of the future, rather than relying on management decisions and corporate strategies to be based on intuition and guesswork.
Advantages of data mining
They help manager and decision makers to predict future situations.
Effective use of data allows businesses to understand their customers better, which helps to improve customer relations.
Being able to make more informed decisions enable businesses to increase sales revenue.
Improved risk management as data mining can be used to detect fraudulent activities and unusual financial transactions. It helps firms to identify potential risks and enhance security measures to protect their assets.
Data mining techniques cut wastage and inefficiencies in operations management, thereby helping businesses to reduce costs, e.g., it enables firms to improve sales forecasting and optimize stock (inventory) levels.
Overall, data mining methods enable businesses to reduce risks and exposure to fraudulent behaviour.
Data mining disadvantages
Privacy issues are a growing concern due to the increasing amount of data about private individuals on platforms, such as social networks, e-commerce, online forums, and smartphone apps.
Security issues surrounding hackers gaining access to big data of customers, including data on personal and financial information, credit card fraud, and identity theft.
Personal data can be collected and misused, including the unethical sale of private information to third parties. The information can be used unethically to take advantage of vulnerable people or to discriminate against a group of people.
Data mining is challenging and complex. Finding the right or required data is a time consuming and difficult task given the huge volume of data present, which are also generated continuously.
It can be highly expensive, including the need to invest in advanced data mining technologies and hiring specialist technicians. Staff training about the use of mined data may also be required, which further increases costs.
What is MIS
is a collective term used to describe the advanced computer technologies and technological innovations that influence business decision-making and stakeholders of a business.
The benefits of management information systems (MIS) and technological innovations on business decision-making and stakeholders include
Improved decision making - Using advanced computer technologies such as artificial intelligence enables a business to automate and improve decision-making. For example, data analytics can provide managers and employees with an in-depth understanding of an organization’s performance, allowing them to make more informed decisions. Furthermore, predictive data analytics can help to provide insights into potential future outcomes, thereby allowing for more confident decision-making.
Better operational efficiency - MIS and technological innovations can be used to streamline processes and reduce costs due to the improved operational efficiency. This has the potential to improve the profits of the business as well as provide better services to its various stakeholders groups.
Improved customer services - MIS and technological innovations can be used to track customer data, such as purchasing habits and preferences, thereby providing vast amounts of data. This provides this business with valuable insights into customer behaviours and their changing needs and wants. Furthermore, MIS and innovative technologies can provide a business with real-time customer feedback, such as through the use of chatbots (or virtual assistants). In turn, this can be used to improve customer services and product offerings, as well as enhancing customer loyalty programmes.
Enhanced competitive advantages - By using the latest MIS and technologies, businesses can gain more insights into their competitors and the markets in which they operate, thereby identify potential threats as well as opportunities for innovation. For example, a business can use predictive data analytics to gain a better understanding of consumer behaviours and trends, which can then be used to develop new products that better meet the changing needs and preferences of customers.
The risks of MIS on business decision-making and stakeholders
Cybercrime - This refers to any form of illegal activity carried out using electronic methods to deliberately and maliciously attack computer hardware or software, including databases, computer devices, and critical infrastructures. With large volumes of big data and sensitive information about customer and employees, there is always the potential risk of unauthorized access, malicious attacks, or data theft.
Set-up and maintenance costs - It can be extremely costly to instal and upgrade management information systems, such as artificial intelligence, customer loyalty programmes, cycbersecurity, and virtual reality (VR). Additionally, training must be provided to staff to ensure that they are able to use the MIS and technologies correctly and efficiently, although the costs of training can be high.
Regulatory compliance - There are legal and regulatory risks associated with the use of MIS and technological innovations. For example, the General Data Protection Regulation (GDPR) requires all businesses operating in the European Union (EU) to protect the data of their customers. Failure to comply with the regulations can lead to significant financial penalties.
To prevent risk of cyberattacks what can business do?
Using firewalls (computer security systems that monitor and control incoming and outgoing network traffic), intrusion detection systems, anti-virus software, and multi-layered data encryption.
Providing ongoing cybersecurity training for managers and employees on the use of the data security systems and cybersecurity measures.
Creating and maintaining detailed and updated contingency plans (backup plans) in the event of a system failure or data breach. These plans can businesses to recover any lost information as quickly as possible, minimize the risks to their stakeholders, and ensure business continuity.
Ethical considerations of MIS on business decision-making & stakeholders
It is important for a business to think about how it will gain the trust of its customers when the time comes to ask them for their personal data, such as their names, contact telephone numbers, emails, and home addresses, for example. MIS and technological innovations can have both positive and negative ethical implications for businesses and their stakeholders.
A business should make sure it only collects and holds what it needs.
Hence, a business should know what personal data it has about customers, suppliers, and employees (such as the name, date of birth, and home address of its employees). The business also needs to tell these stakeholders what it plans to do with the data.
The data must be securely stored (such as a secured database or cloud computing platform. The data must also be disposed of safely and and when appropriate.
The business must respect people’s data privacy rights.
Improved decision making - MIS and technological innovations can help businesses make more informed decisions and better serve their stakeholders in an ethical way. For example, MIS allow businesses to collect customer data to better understand their needs and preferences, leading to improved customer services. Such decisions are made more objectively, without the potential of human bias in the decision making process.
Other ethical considerations of MIS and technological innovations on business decision-making and stakeholders, such as employees, include the following points:
Improved decision making - MIS and technological innovations can help businesses make more informed decisions and better serve their stakeholders in an ethical way. For example, MIS allow businesses to collect customer data to better understand their needs and preferences, leading to improved customer services. Such decisions are made more objectively, without the potential of human bias in the decision making process.
Data manipulation - This refers to the deliberate misuse of data in order to influence a particular decision or outcome. Hence, data manipulation is unethical, especially if is intended to mislead or deceive. Examples of data manipulation include deliberately and intentionally adding or removing data, changing data values, or misrepresenting the data.
Lack of human touch - MIS and innovative technologies rely on automated processes and make decisions based on algorithms and computer programmes, which can eliminate human input in the process. This means there is an absence of emotions and empathy in decision-making, which can be unethical even if it follows the protocol and policies of the organization.
