Mgsys 101 - Lecture notes 1-12 PDF

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Lecture OneWhat is digital business?Digital business is everyone’s business (Lopez, 2014) Automation, robotics, cloud technology, etc Digital business explores the way people and organisations operate, interact,communicate, cooperate• Digital technologies change the way we work and interact Digital ...

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Lecture One Thursday, 5 August 2021

1:32 pm

Lecture One What is digital business? Digital business is everyone’s business (Lopez, 2014) • Automation, robotics, cloud technology, etc • Digital business explores the way people and organisations operate, interact,

communicate, cooperate • Digital technologies change the way we work and interact

Digital transformation • New ways of doing business and creating value for customers • Using technologies to automate business

What is supply chain management? • Managing and coordinating the movements of goods, e.g. from the farm to the table • Making the goods available at the right time at the right place. Session 01 - Introduction to Systems Thinking Integrated Thinking (Systems Thinking) • Integrated Thinking is an approach to problem solving. • It encourages managers to understand the relationships between related, and seemingly unrelated parts of a problem. Is also referred to as “Systems Thinking” What is a System? • A system is any group of interacting, interrelated or interdependent parts that form a complex and united whole that has a specific purpose. If parts are not interacting, theta are simply a collection. Eg - tools in a tool box, simply a collection of tools. • In Conclusion, a system is a whole consisting of a set of two or mor4e parts. Each part affects the behaviour of the whole. It also depends on the interaction of parts. A car not the sum of its parts, but the product of the parts interaction makes it a system. Principles of Systems Thinking Management approach to understanding complexity and change within the organisational ecosystem. (A holistic way of understanding how organisations work within the construct of society). • Systems Thinking Paradigm • Big picture thinking • Dynamic thinking • Operational thinking • Closed-loop thinking

Systems Principles Big Picture Thinking: Can see the whole picture as well as focus on the details. The ability to

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see the big picture and how the component parts relate and interact. Dynamic Thinking: Recognising that the world is not static and that things change constantly. Operational Thinking: Understanding the ‘physics’ of operations, and how things really work and affect each other. • A focus on how things work. • Understanding the interrelationships of functions in an organisation Closed-loop Thinking: Recognising that cause and effect are not linear and that often the end (effect) can influence the means (cause). Closed-loop thinking skills lead you to see causality as an ongoing process, rather than a one-time event. • Causes may not necessarily be linked to outcomes (cause vs effect) • Time and space: Effects occur after a period of time which may not seem to be linked to original causes • Fixes that fail • Unintended consequences Other systems principles • Short and long term: short term fix effects long term results over time. Fixes that fail • • • •

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and unintended consequences Soft indicators: Subjective things that indicate a problem might exist. Examples: Unlimited sick leave costing/causing problems. Staff turnover, morale, loyalty System as a cause: System or processes causes behaviour Time and space: after a delay, unintended consequences not necessarily linked to the original cause. e.g. the butterfly effect Cause vs. symptom: when something goes wrong, focusing on the symptom, not the real cause. E.g. Ambulance at the bottom of the cliff. Look at WHAT is happening, not WHY it is happening. Either-or thinking: About perspective, reframing, not always a right or wrong answer

Why is Systems Thinking needed? • Increasing complexity in the world • Growing interdependence of the world • Critical need for change • Mutual interdependence • Common heritage and destiny for mankind Analysis Thinking vs Systems Thinking

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Digital Business – What is it? Digital business is the creation of new business designs by blurring the digital and physical worlds What makes digital business different from e-business is the presence and integration of things – connected and intelligent – with people and business. What are digital technologies? Some examples: • Electronic equipment and devices • Applications • Infrastructure • Networks Digital technologies store, generate, process, and transport data across interconnected networks. Moore’s Law An observation, and a prediction: “The number of transistors per square inch on an integrated chip doubles about every two years” (Moore, 1965) • Computer chip performance will double every two years, and Chips become smaller, and cost less to manufacture Moore’s Law in action: “Today, your cell phone has more computer power than all of NASA back in 1969, when it placed two astronauts on the moon” Dr Michio Kaku (2017). Impacts of Moore’s Law

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¢Are there limits to Moore’s Law? Based on the End of Moore’s Law reading, answer the following question: Do you think Moore’s Law still holds true today?

An ERP System is the implementation of digitisation of paper-based records to improve processes digitally. All aspects of a business are digitally connected and interrelated. The digitalisation enables digital transformation through the introduction innovative new technologies (e.g. Robotics and AI)

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Lecture Two Thursday, 5 August 2021

2:15 pm

Lecture 2 - MGSYS101 – S03 Digital Transformation, Digital Disruption 4th Industrial Resolution: Internet of Things

Case Study: Digital Transformation How does enterprise resource planning support digital transformation? Reading - digital transformation isn't about ERP anymore, it's about automation with machine learning. • Enterprise resource planning systems • Centralized and integrated management of day to day business activities. • All data in a single database leads to information sharing. • Centralized data can be used to create and share reports, which improves management decision making • ERP systems can lead to increased automation • ERP systems underpin digital transformation • Digital transformation is the process of moving from information to automation. What is a disruptor? • Something that uproots the status quo and transforms the way we live and work What are some examples of business disruptions? ○ Physical CD/DVD stores into website that you can watch movies and television shows. ○ Netflix used to send DVD's to houses and have now changed their way of business by developing a website where users can watch their favourite shows and movies through a monthly subscription. The company has disrupted the television industry and cinema industry. Other alternatives have disrupted Netflix as well such as neon and Disney plus. Netflix has made their own content that has made exclusive to them and gain competitive advantage in the industry. Digital Disruption: Definition and meaning

For technology to be considered a digital disruption, it has to meet the following qualities: Lectures Page 5

• It has to be disruptive – a threat to an incumbent’s business goals in short or long term • It has to be digital. For example, a new technology such as artificial intelligence, or

augmented reality. • It Challenges traditional business models, and has enormous consequences for traditional business within an industry Discussion: How does Uber demonstrate digital disruption? ○ Identify customer experience gaps across multiple industries (taxi, public transport, food and beverage, cargo). ○ Create a service that combined all these gaps. ○ Then leverage technology and expertise to solve a problem for customers ○ Identify a unique problem, then use technology to address the problem for customers. ○ Digital disruptors are customer focused.

Transformation vs Disruption

Is Digital Disruption still relevant? • “Digital disruption is now just digital delivery” Walsh, 2020 Industry 4.0 A convergence of technologies is evolving into the Internet of Things Disruptive Technologies (Historic) • The first Industrial revolution (c.1760-1840) • The modern factory (1771) • Locomotives (1812) • Telegraph communications (1837) • Photographs (1826) • The typewriter (1868)

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Second Industrial Revolution (1870-1969) Creation of the internal combustion engine • Powers modern modes of transport: vehicles, ships, trains, planes. Third Industrial Revolution (1969-2000) • Computers • Electronics Fourth Industrial Revolution (2000- Industry 4.0). • Internet everywhere • Digital Disruption and Transformation industry 4.0 Leverages: • Big Data and Artificial intelligence • Predictive and prescriptive analytics • Cyber-physical systems • Cloud Technologies – SaaS, PaaS, IaaS • Robotics A convergence of technologies is evolving into the Internet of Things. What is the Internet of Things? The Internet of Things (IoT) is a network of low-powered physical objects embedded with software, sensors and network connectivity that enables these objects to collect and exchange data autonomously. • • • • • •

Low-powered Physical objects Contain sensors Network enabled Collect data Exchange data

What is the Internet of Things? The Internet of Things is essentially a system of interconnected devices. These devices: • Communicate with other devices without human interaction – machine to machine communication (M2M) • Are used in commercial and private settings • Can be everyday devices with embedded sensors • Make use of an extremely wide range of sensors • Communicate over a range of networks • Create huge amounts of data generated in real time IoT in Agriculture • A paradigm shift – everything, connected and working autonomously without human intervention. IoT- Challenges & Benefits

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Cyber-Physical Systems Physical or mechanical systems which are controlled autonomously by computers • E.G. Autonomous automotive systems, medical monitoring, or process control systems. • Industry 4.0 will fundamentally comprise of the “smart factory." IoT and Smart Factories A paradigm shift – everything, connected and working autonomously without human intervention How is IoT demonstrated in this video? (sensors, connecting and exchanging data without humans)

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Lecture Three Tuesday, 10 August 2021

6:24 pm

Session 05 - Big Data and Business Analytics Big Data Definition - “Big Data is high volume, high velocity and high variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation” (Gartner, 2017) Big Data observation: “Data is Big, when the size of the data becomes part of the problem.” Roger Magoulas - Director of Market Research – O’Reilly Media Attributes of big data Volume –  Amount of data, scale Variety –  Range of data types and sources Velocity –  Speed of the generation of new data Analysis – big data requires cost-effective, innovative forms of information processing to enable insight and decision making Characteristics of Big Data: Volume Size is Not the Issue: It is not the size of Big Data that is the primary concern. The most difficult aspect is its lack of structure Characteristics of Big Data: Variety Various formats, types, and structures. Examples include: text, numerical, images, audio, video, sequences, time series, social media data, RFID data, medical data, sensor data, static data vs streaming data In the past organisations relied on structured ‘database’ data such as in a spreadsheet For example - names, dates, addresses, credit card numbers, stock information, geolocation, and more. Unstructured data can include: text, audio, video, radio waves, GPS, anything that doesn’t fit neatly into a spreadsheet Technically, Big-Data in business is semi-structured data as it is a combination of structured and unstructured Characteristics of Big Data: Velocity Data is begin generated fast and needs to be processed equally quickly to be useful Real-time analytics is required a new tools, skills and methods Examples: Predictive marketing: Based on your current location, your purchase history, what you like and send promotions right now for store next to you

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Recap of Big data Characteristics What is Big Data? What are its defining characteristics? Volume: Data volume is increasing exponentially Velocity: Data needs to be analysed quickly Variety: different types of structured and unstructured data Question: Where does all the data come from in Big Data? - Weblogs, RFID, GPS systems, sensor networks, social networks, internet-based text documents, internet search indexes, detail call records, astronomy, atmospheric science, biology, genomics, nuclear physics, biochemical experiments, medical records, scientific research, military surveillance, multimedia archives. Big Data in Healthcare • Benefits - Preventative vs reactive - Reduced healthcare infrastructure costs - Reduced deaths, longer life expectancy

- Fewer cases of preventable disease - Less strain on emergency services • Challenges - Privacy issues - Digital divide: Technology accessibility - Data security issues - Less personal responsibility for health - Increased population/ life expectancy - Ethical challenges Netflix Big Data Case Study • How does Netflix use Big data? Volume: Data includes media storage. There are approximately 105 terabytes of movies stored Netflix' servers, there are billion s of ratings on Netflix, 10k GB of rating data, Velocity: 1 million subscribers and 159 million viewers Variety: most of the data is structured such as day, viewer, duration, time. However, Netflix is probably also using unstructured data, stating that thumbnails for each video may be different for different people. • What different types of data does Netflix collect? - Stream related data such as duration, time of playing, type of device, day of the week. - Millions of genre and media titles users add o their queues each day - Data includes users streaming data - All the meta data about a title such as director, actors, ratings and reviews - Rating system allows for collaborative filtering, and relies on the concept that people who have lies something in the past would probably like the same experience in the future.

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- Data about users such as demographics, culture, language. • What Does Netflix do with all this data? - It generates playlists - Recommends products to its customers in app and via email. - Encourages continued use • How does Netflix monetise this data. - Netflix income is derived from subscription

What is Business Intelligence and Business Analytics? Business intelligence – The process of collecting, storing and analysing data from business operations. ○ Valuable information from variety of sources. Business intelligence creates knowledge for better decision making within an organisation. ○ Good information must be accurate, timely, relevant to context and subject, just sufficient, and worth its cost.

Business analytics – refers to the practice of using your company’s data to anticipate trends and outcomes. ○ The technical process of mining data, cleaning data, transforming data, and managing data for analysis is called data analytics Types of Business Analytics Descriptive Analytics ○ Explains what has happened ○ Business Intelligence prioritises descriptive analytics using data aggregation and data mining to provide insight into the past ○ Describe and summarise raw data to make it interpretable by humans ○ Descriptive analytics are useful because they allow us to learn from past behaviours and understand how they might influence future outcomes. Diagnostic Analytics ○ Explains why something happened. ○ For example, for a social media marketing campaign, you can use diagnostic analytics to assess sudden changes in site visitor activity. ○ Diagnostic analysis takes the insights found from descriptive analytics and drills down to find the causes of those outcomes. Predictive Analytics ○ Explains what might happen ○ Predictive analytics use statistical models and forecast techniques to understand the future based on probabilities.

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○ Predictive analytics combine transactional and historical data such ERP, CRM, HR and POS systems to identify patterns in the data and apply statistical models and algorithms to capture relationships between various data sets. ○ Predictive analytics are used to predict likely outcomes Prescriptive Analytics ○ Recommends an action based on the forecast ○ Prescriptive analytics use optimisation and simulation algorithms to advise on possible outcomes and recommend best outcomes ○ Prescriptive analytics attempt to quantify the effect of future decisions in order to advise on possible outcomes before the decisions are actually made. ○ Prescriptive analytics links with autonomous decision making, artificial intelligence, automation and robotics. By allowing machines to make the decisions and take actions.

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Lecture Four Tuesday, 10 August 2021

6:24 pm

Session 07 - Digital Workplaces and Enabling Technologies Cloud Computing, Internet of Things, Artificial Intelligence

What is Cloud Computing? The practice of using a network of remote servers hosted on the Internet to store, manage, and process data, rather than a local server or a personal computer. • Computing processing power • Data storage • Networking • Development platforms • Deployment platforms • Business processes Cloud computing is the enabling technology of all digital business Example - google - Google stores and manages data of their users.

Common Cloud Service Models Three key service models are: • Software as a Service • Platform as a Service • Infrastructure as a Service

Essential characteristics of Cloud Computing • On demand, self-service • Flexible pricing • Rapid elasticity • Resource pooling • Ubiquitous access

Advantages of Cloud Computing • Lower Computing Cost • Reduced Cost of License Agreements • Improved Performance • Reduced Software Cost • Instant Free Software Updates • Unlimited Storage Capacity • Increased Data Reliability

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• Device independence and access is always available • SaaS does not require a great amount of technical knowledge

Cloud Deployment Models Public Cloud - Owned and managed by service provider (e.g. Google Cloud, Microsoft Azure) - In a public cloud, you share the same hardware, storage, and network devices with other organisations or cloud “tenants,” and you access services and manage your account using a web browser. Private Cloud - A private cloud consists of cloud computing resources used exclusively by one business or organisation. - Single-tenant architecture ○ Example: IBM, HP, Ubuntu, Dell Community Cloud - Shared infrastructure by several organizations which have shared concerns - Example: IBM SoftLayer cloud for federal agencies; NZ Government: DIA, MSD Hybrid Cloud - Composition of two or more clouds (private, community, or public) bound together by standardized or proprietary technology that enables data and application portability.

Case Study - Westpac Which deployment method of cloud computing is used by Westpac Bank? - Hybrid model - private and public ○ Westpac’s new private offsite cloud is powered by VMware in two IBM Cloud data centres in Australia to meet APRA compliance regulations. When combined with the bank’s existing on-premises infrastructure and public cloud services, the bank has a single platform for greater flexibility and operational efficiencies What are the benefits to Westpac Bank of cloud computing? - Technology is kept up to date, as IBM updates on their behalf. IBM Scales services up and down automatically on demand, so they benefit from rapid elasticity. It also leads to increase process automation for Westpac. It allows them to tes...