Module 1 PDF

Module 1: Norman's dematerialised model consists of Dematerialization on the top, Liquidity on the left, Unbundleability on the right, Rebundleability at the bottom, and below that is Density. Dematerialization: the removal of physical attributes, in favor of non-physical ones. (example: convertin...

Module 1: Norman's dematerialised model consists of Dematerialization on the top, Liquidity on the left, Unbundleability on the right, Rebundleability at the bottom, and below that is Density. Dematerialization: the removal of physical attributes, in favor of non-physical ones. (example: converting texts from ink to binary code) Liquidity: the consequence of separating information from the physical world, allowing to be moved around. (example: viral memes) Unbundleability: seperation of activities that are well defined and held together in time and place by actor. (example: distance teaching) Rebundleability: combining the liquid, unrestrained assets with others in new ways to create new business models. (example: learning apps (replacing teachers with content creators and algorithms, replacing classrooms with phones)) Density: combination of resources that are mobilised for a particular situation to create optimal value. (example: airbnb vs hotel chains) Example of Norman's dematerialised model: A musician makes a song. In old days, the song would have been a single on a physical vinyl record. Now it's recorded digitally, so it is already dematerialized and digital copies of it are seperated from the main copy. Because of liquidity, the song is able to go anywhere, on platforms like spotify or apple music. and because of unbundling, artists can make money from these platforms. You can also rebundle this into an album, or playlist. Service-dominant logic: Based on the belief that products / services only become valuable when consumers use them. Goods - dominant logic: Based on the belief that the value of products come from resources that business used to produce them. Fundamentals of service-dominant logic: - All exchanges in the economy are service-to-service exchanges - The provider and costumer both co-create value, since customers allow businesses to recognize what is needed in the market - Business supplies service, and customers use service to improve their life. - Uses of intermediate sources of value (money), make service-to-service exchange hard to see - The value of products don't come from the ownership, but from the service they provide (example: when you buy a toothbrush, the value of the toothbrush won't come from the product itself, but from the service it does) - it is easier to improve the product when you understand the job Module 2: What to digitise: (For products): - User experience: Digital products / services can offer high levels of usability, have aesthetic features and be engaging. - Value proposition: Digital innovation, with strategic pricing and portfolio, building of product units, and selling. (For environment): - Digital evolution scanning: To identify opportunities for innovation, firms need to scan their digital environment, by gathering info on new digital devices, channels. (For organization): - Skills: To enjoy the benefits of digital innovation, firms need to get new internal and external skills for their digital operations. They should have innovative team, - Improvisation: Digital technologies are malable, managers need to ensure they provide employees with time and space to innovate. Disruptive innovation: It is the process where a smaller company (entrant) with fewer resources, effectively challenges a larger, established business (incumbent). Sustaining innovations: They are incumbents that improve their products along time according to customer values, to allow them to sell better products at higher values, rather than focusing on entrants. How does Disruptive innovation work? - Incumbents often outpaces customer demand preferences just for their own performance improvements, which leaves a gap in the lower-segment of market where their needs are not met, but high-end is met. Therefore, new entrants exploit this gap by targeting the low segment market, offering disruptive innovations, that are less powerful but offer different values. As this disruptive innovation succeeds and improves, it will eventually not only meet the low segment market needs, but also the mainstream customer needs, therefore competing with the incumbent's market share. Eventually, the mainstream customers will adopt the entrant's offerings into large numbers, and disruption would have occurred, incumbents will struggle to catch up to entrants. Why do incumbents overlook entrants: Incumbents prioritise projects that are high margins, larger and better markets that prefer sustaining innovations. Incumbents also mostly focus on short term returns and don't pay attention to long-term returns or challenges. Module 3: Types of AI: - Narrow / Weak AI: AI currently, Only able to focus on performing one task. It's subset is Machine Learning, which consists of algorithms and neural networks. Machine Learning's subset is Deep Learning. - General AI (AGI): Future development of AI, will be able to do all the tasks that humans can do. - Super AI (ASI): Future development of AI, will be smarter than humans and do more. The Moat: In business, the moat is a sustainable competitive advantage that companies have against their customers. Dancing bearware: You aren't impressed that the bear is dancing well, you are impressed that it is dancing at all. Same with AI. Turing test: Used to determine how machines think. Test involved a human guessing if the response he received was by another human or by a machine pretending to be human. However, turing test is not as good as it promotes trickery and also does not take into account for non human intelligence. Difference between Machine Learning and Deep learning: - Machine learning involves learning the behaviour of humans. and it contains structured data with labels on what you want to identify. Deep learning contains unstructured data, with no labels, and it is up to the machine to group the data into labels. Large language models: Help computers understand the language, dialogues, memes. Helps computer understand meaning behind language. The Stochastic parrot: A model that is training on large datasets, used to predict what will most likely be the next word in given sentence. The Hallucinations: What happens when large language models gives false information because they don't have an understanding of the underlying meanings in the language. External impact areas: - Privacy: AI has so much data on us, even private data. - Sustainability: Footprint used to generate 1 chatgpt response is so much larger than just 1 google search. - Truth: Students don't know what is fake news and real news on social media. - Inclusion: Tesla not detecting black people due to biased data. - Health: Instagram causing health risks (depression) to people. Internal impact areas: - Work: Humans hiding behind fake AI chatbots in companies. - Comms: AI - free content deserves a badge. - Value: AI discovery in healthcare. - Identity: AI plagiarising from other people's work. - Risk: Scientists created AI to develop sexual harassment in emails. Module 4: Digital Leadership key points: 1) Confusion over what digitisation leadership means: - It is not just the introduction of digital technology in an organization, such as introducing a new app, installing software, small initiatives to increase efficiency. It means digital transformation. Therefore, digital leadership is more about what we are unbundling and rebundling in the system. 2) Poor digitization: - Companies can have Piecemeal initiatives (which is when different departments in the company have small digital transformations, without thinking about the whole organization and how it will impact it). A good digital leader would not do this, they would instead think about the whole organization. - Companies can also have Missed opportunities. Companies need to think about what opportunities have opened up because of this technology integration. 3) Good digital leader would use these strategies for implementation: - Clear strategy (simple and clear) - Holistic (considers the whole organization) - Well-communicated strategies V.U.C.A.: - Volatile: Describes how we live in a world that is constantly changing. This can hard when implementing strategies, since what works today might not work tomorrow. - Uncertain: Describes how we can't predict what will happen in future. Theretofore, you need to plan effectively and think about what long-term strategies to invest in. Who should we think about hiring with what kind of skills, even though we don't know what kind of skills we will need tomorrow. - Complex: It is getting harder to understand the relationship between companies. Therefore it is harder to strategise. We need to think about who are our competitors, who will our competitors be in the future if they found a technology that allows them to bridge into our market and compete with us. - Ambiguous: Describes how definitions, roles, and boundaries in market are all unclear. Is this new company that we see a non-threat or is it an entrant? How can organisations succeed in V.U.C.A.? - Through dynamic capabilities, which enable you to understand and adapt to your environment. Dynamic capabilities: 1) Ability to sense change: Organizations need to be able to anticipate what will be next in an unpredictable world. 2) Seize opportunities: Organizations need to be able to seize opportunities, and interpret the data. They also need to be able to have decision-making capabilities based on the data. 3) Transform the firm: Organizations need to be able to align with the changes in the environment, and learn from processes and mistakes. Structural rigidities: When building a structure in an organization, Incumbent firms face structural rigidities that prevent them from adapting to their environment. Incentive structures: - It is when organizations are incentivised to do business as usual, and not change. Therefore, you are incentivised to keep doing the same thing, because they think that since this way of doing things have worked in the past, it will keep on working in the future too, so they don't need to change. Negatives of incentive structures: - There can be lag effects in customer demands: If the customer suddenly wants to change the way they do things, they can do that in a second. But it takes time for the organization who are delivering the service to change the processes (creating a lag effect). - Perverse KPIs: If organizations have KPIs that incentivize us to get return on investments by continuing to sell the product, employees are being incentivized to not change the way they do things. This can prevent employees from taking risks in the future and trying new things, which can also prevent people from looking at the long-term return on investments. - Culture of fear: Middle-managers can be scared to make decisions, or tell top managers that there is something wrong in the company's operations and that they should change the way they do things. Attention structures: - It is when organizations can determine a firm's behaviour by looking at what they are paying attention to. However, this can be bad since people don't realize that they don't have free thinking, and that unconsciously, your thinking is always directed by external force. Static structures: - It is when organizations rely on tacit knowledge of employees (meaning that if it is an IT organization, they need to have people who are very good at coding). By doing so, if you have the best person in the field working at your organization, you will have a competition advantage. Static structures negatives: - However, having employees who are only good at one specific field with niche skills can be harmful for the organization in the long-run, as it can make you resistant to change and inflexible. In the case that your oragnization transformed to another field (example: moved from IT services to streaming media services), then the employees would know nothing about it, therefore it is important to train your organizations to transition more smoothly into the new field. Identity structures: - Often times, organizations have a collective identity. But this can also mean that they have a clear "we don't do this" identity. This can create barriers to try new things, expand to new sectors, and miss out on opportunities.