Fundamentals of Digitalization Summary PDF

Fundamentals of Digitalization Lecture 1: Implications of the digital transformation – an introduction Wall Street envisions the largest potential in new, digital businesses à established firms feel forced to adapt Artificial intelligence likel...

Fundamentals of Digitalization Lecture 1: Implications of the digital transformation – an introduction Wall Street envisions the largest potential in new, digital businesses à established firms feel forced to adapt Artificial intelligence likely to affect society at large (exponential scientific progress) Harari suggests three ways to cope with the AI progress: 1. Lifelong learning to adapt to constantly changing requirements 2. Test cases for making possible future predictions 3. Developing a new economic system to compensate for the many jobs replaced by AI Digitization, Digitalization and Digital Transformation o Can be defined in a variety of ways, e.g.: Lecture 2: Challenges of digitalization for established actors and systems Digitization à changes in strategies like Representation, connectivity, and aggregation: Four major aspects of representation: o Information conversion o Datafication of new information o Digital-to-physical transformation o Machine learning / algorithms Four main shifts in connectivity: o One-to-one à many-to-many o Connectivity on demand à Connectivity by default o Is it right? à Is it relevant? o What do I know? à What do I ignore? Aggregation: Combine formerly disjoint data o Benefits: § Deeper understanding of organizational structures § More complex assessments (e.g., credit scores) § New insights to individual needs o Risks: § Higher level of surveillance by corporations / governments § Possible unethical usage of data Þ Many (more) firm strategies are heavily influenced by the digital transformation Characteristics of data: Scale-free, autogenic (act of engaging with data generates data), fungibility, cost-free replicable, can be sold and kept at the same time Questions about data: Data ownership, consent, access to data, re-usage of data  Scalability of a firm improves significantly when it uses connectivity and aggregation Digital transformation and the internal organization of firms: Four competitive processes that can induce the decline of an incumbent firm: 1. Internal dysfunction 2. Competitive rivalry 3. Substitution (new players) 4. Commoditization Some companies might always retreat into the niche of recreation (e.g., Luxury watch companies in times of digital watches, Ferraris vs. Tesla, etc.) Disruptive innovations: o New bundles of customer value in existing value dimensions (Amazon) o New architectures for transforming inputs into outputs (IKEA) o New revenue structures (iTunes, AirBnB) Incumbent inertia: “Difficulty of established players to enact internal change in the face of significant external change.” Business ecosystem: “Consists of a dynamic group of independent economic players that create products or services that together constitute a coherent solution.” “Characterized by a specific value proposition (desired solution) and a clearly defined group of actors with different roles (supplier, producer, etc.) Ecosystem characteristics that set them apart from vertically integrated supply chains: o Modularity (Components designed independently yet function as a whole) o Customization o Multilaterism (Complex, multilateral interactions) o Coordination (Not fully hierarchically controlled) Four central shifts in the automotive industry: 1. Connected 2. Autonomous  o Six Levels 0-5 à no steering wheel/paddles as level 5 o Problem: Requires costly hardware and complex software 3. Shared 4. Electric / other sustainable energy forms Digital platforms are challenging complementors: Trigger commodization and enable substitution Platform envelopment: “Platform gradually enters market, learns and then moves into further market segments.” (e.g., Netflix moves into film / show production) Risk of value inversion: Complementing good becomes too good and undermines the need for the old (e.g., Telephone and telegraph) Tesla – viewed by investors as an aggregate: Lecture 3: Industrie 4.0 Industrie 4.0: Vierte industrielle Revolution Mechanisierung, Automatisierung, Digitalisierung und Vernetzung industrieller Infrastruktur Ist die Industrie 4.0 evolutionär oder revolutionär? „Verfügbarkeit aller relevanten Infos durch Vernetzung aller an der Wertschöpfung beteiligten Instanzen.“ Smarte Produktionsprozesse à Internet of Things à Internet of Everything? „Race against the machine“? bei dem der technische Fortschritt viele Arbeiter hinter sich lassen wird Trends der Digitalisierung der Industrie: 1. Internationalisierung der Märkte 2. Rückgang der Fertigungstiefe (Auslagerung von Produktion) 3. Dezentrale Steuerungskonzepte und stärkere Prozessorientierung 4. Mass Customization 5. Open-Innovation-Concept 6. Verkürzte Produktlebenszyklen Þ Wettbewerbs-, Kosten- und Produktionsdruck Wirtschaftlichkeitseffekte: Solow Paradox: „IT-Investitionen sind überall sichtbar, aber in ihrer ökonomischen Wirkung kaum messbar.“ Ergänzende Investments zur Organisation und Produkt-/ Prozessoptimierung können IT-Investitionen wertvoll machen Erfolg von Daten- und Produktplattformen Viele neue digitale Geschäftsmodelle o Digitale Disruption alter Geschäftsmodelle Eigenschaften digitaler Produkte / Informationen: Vier Funktionalitätsstufen: Überwachung, Steuerung, Optimierung und Autonomie Fazit der Industrie 4.0: Industrie 4.0 = „Form industrieller Wertschöpfung, die durch Digitalisierung, Automatisierung sowie Vernetzung aller an der Wertschöpfung beteiligten Akteure charakterisiert ist und auf Prozesse, Produkte oder Geschäftsmodelle von Industriebetrieben wirkt.“  Zwei grundsätzliche Gestaltungsoptionen für Unternehmen: 1. Betriebswirtschaftliche Nutzung der Digitalisierung à Steigerung von Prozesseffizienz und Wettbewerbsfähigkeit 2. Entwicklung intelligenter, innovativer und/oder disruptiver Produkte und Geschäftsmodelle Lecture 4: Data Science Data Deluge: Information and digital data have been growing exponentially o 2020: 5200 GB or 500 tons of books per human on earth Internet as main driver, but most of the info is unstructured and hard to process Value of data: Creating insights from data for companies, research, etc. o “Data is the new oil.” From Data to knowledge: Data Science Definition: “Researches and applies technologies, systems and algorithms to gain knowledge from potentially large, heterogeneous and dynamically changing data sets.” Knowledge: Deductive Reasoning: Given a premise, we infer new facts / a conclusion through applying logical rules Inductive Reasoning: Given patterns, we try to identify regularity in the patterns and derive facts from it Knowledge Discovery in Data = KDD Process: Before analyzing data is has to be selected, cleaned, integrated and preprocessed o Querying: Only take proper subsets of the data instead of the whole data o Transformation: Prepare the data for the algorithm Three types of Analysis: 1. Descriptive Analysis 2. Explorative Analysis 3. Predictive Analysis Interpretation: Finally, we have to judge the value of the generated knowledge Neural Network Examples: Slides 50+ Skills and Applications: Data science requires skills from three fields + skills from the domain at hand (Business, research, etc.) Lecture 5: Optional Lecture 6: Leveraging Value Contributions from digital customers Limitations of classical Customer Lifetime Value (CLV) Definitions: Classical definition: “Net of the revenues obtained from that customer over the lifetime of transactions minus the cost of attracting, selling and servicing that customer, taking into account the time value of money.” Strong focus on direct revenues à not applicable to all business models Can lead to major misjudgments of actual customer value Free digital services like Instagram, etc. are perfect examples as to how valuable customers can be, even if they do not provide direct revenues. Þ Customer Value as a dual concept: Provide value to customers and extract value from customers Types of value from customers: Transaction revenues, consumer attention, co-production, word-of-mouth, network effects, consumer data, etc. Intrinsically vs. extrinsically motivated word-of-mouth Negative- / Positive- and Direct- / Indirect network effects Three major types of Co-production: Data is generated through: Voluntarily submitted-, observed- and predicted data Managing Customer Value: Digital goods require value to more than one customer group Digital firms / platforms often operate in two- or more-sided markets Many pricing approaches miss out on indirect customer value à risk of overpricing Current research on customer value: Systems thinking: “The understanding of the relevant actors and their interdependencies + the subsequent design of concrete customer orientation activities to one group that benefit the other customer group.” “Free” is just a psychologically special price Take-aways: Lecture 7: - Lecture 8: Pricing of digital innovations Digital innovations: “Product, process or business model that is perceived as new, requires some significant changes on the part of adopters and is embodied in or enabled by IT.” Can destroy established business models and disrupt existing value chains New opportunities for business: o Use digital tech to enhance traditional business models o Transform existing business models o Invent new business models Patterns of monetizing failures: Feature shock: Too many / wrong features in one product Minivation (underpriced) Hidden gem Undead products (Answers to questions no one asked) Þ Put the price and the customer’s willingness to pay for a new product / service at the very core of the digital innovation design! Forms of price determination: Non participative pricing: Difficulty: What is the optimal price? Advantages: Easy to communicate, no negotiation costs, easy to monitor / implement Participative and interactive pricing: Don’t necessarily replace all fixed prices Difficulty: What is the optimal design? Advantages: Direct customer contact, price perceived as innovative, low price- transparency, higher average prices and market efficiency How to price digital innovations: Subscription models: Purchase decisions do not have to be made repeatedly Companies often offer lower prices in return for continuous cash flows Choice between Flatrate vs. price based on usage Dynamic pricing: Optimizes pricing with respect to objectives like price differentiation and to increase corporate revenues Question: What is the individual WTP à “fair” price for customer Freemium: Land and Expand Basic version is free in the hope customers pay for the premium version Attracts high volume of customers à paying customers generate revenue Name your own price / reverse pricing: Seller determines a price threshold unknown to buyers  Buyers indicate max. WTP Purchase is made when price offered by buyer is at least as high as price threshold by seller (Buyers do not compete directly with their bid) Þ Summary: Lecture 9: Digital Platforms & Business Strategy Same-side Network Externalities (phones) vs. Cross-side N. E. (eBay Sellers / Buyers) Chicken-or-Egg dilemma: Most platforms fail because of a lack of cross-side externalities 8 Strategies for beating the dilemma: 1. Follow-the-rabbit o Converting a successful running business into a platform (Amazon marketplace) 2. Piggyback o Using an existing user base of another platform (YouTube on Myspace) 3. Seeding o Create value relevant to at least one set of users à other sets who want to interact with these users will follow (Adobe) 4. Marquee o Provide incentives to attract members of a key user set onto the platform (PlayStation) 5. Single-Side o Create business that benefits a single set of users à second set will follow attracted by the prospect of interaction with the first (Facebook and ad companies) 6. Producer Evangelism o Attract producers, who can induce their customers to become users of the platform 7. Big-Bang Adoption o Push marketing strategies to attract a high-volume interest and attention to your platform (Tinder) 8. Micro market o Targeting a tiny market of members who are already interacting (Beginning of Facebook) Viral growth: Complement to the presented launch strategies Pull-based process on encouraging users to spread the word about the platform  Critical Mass: Point where viral growth is so strong that launch strategies are not necessary anymore Four key elements needed to trigger viral growth: 1. Sender 2. Value Unit 3. External Network 4. Recipient 1. The Sender Spreads value units Talks about his own creations on the platform not the platform itself It must be easy for the sender to share value units with new potential customers 2. The Value Unit: Embodiment of the platform usage Demonstrates the platform’s value for external users It should be possible to spread the value unit across external networks (Not every value unit is spreadable, e.g., documents on a business platform à Viral growth strategy cannot be used in this case) 3. The External Network Create value-adding ways to connect with other network’s users (Be aware: External Networks often introduce restrictions when more and more apps use them for growth.) One can avoid risk and attract new customers by piggybacking on a not common external network (LinkedIn with Outlook) 4. The Recipient When value units are intriguing enough, the recipients spread them further Since value units are created by users, managers oh platforms have limited control over them and their quality If possible, platforms should nudge users in directions that will make value units more attractive to recipients and / or implement social feedback mechanisms Þ Take Aways: Lecture 10: -  Lecture 11: The economic impacts of digital information- and communication technologies ICT in Africa Africa has substantial deficits in terms of infrastructure Yet, mobile phone telephony has increased dramatically à Provides cheap access to information, markets, and services o Reasons: Young people have a higher propensity to adopt new products + network effects There’s a digital divide between the average 4G coverage (62%), the Northern Africa 4G coverage (87%) and the Western Africa coverage (59%) Also, mobile banking in Africa has increased by nearly 200% Big tech starts investing in Africa à Artificial Intelligence Research centers, product development centers à Education of six million people Why will ICT enhance economic development? 1. ICT can provide Info, reduce search costs, improve coordination among agents and increase market efficiency 2. ICT allows firms to better manage their supply chains 3. ICT can facilitate communication among social networks in response to shocks 4. ICT can facilitate the delivery of financial-, agricultural-, health- and educational services 5. ICT creates new jobs to address demand for ICT services Challenges and Conclusion: Electricity and Infrastructure problems High expectations on ICT based on assumption that the Info provided is of high quality (often not the case) Þ “ICT offers a lot of potential, yet is not a silver bullet and cannot replace investments in public goods such as education, power, roads and water.” Lecture 12: Crowdsourcing Crowdsourcing characteristics: “Open call” challenge with prize Surprising winner that the organization could not have asked for help Through digitalization, crowdsourcing has become much more powerful Examples: Wikipedia became far more successful than predecessor Nupedia because it changed to a more open system) DARPA is noted for its innovation in military and civilian fields o Avoid putting military drivers in danger à challenge for start-ups in autonomous driving à Several successful results influenced urban autonomous driving How does crowdsourcing work? Successful crowdsourcing demands a solid framework to guide the project Areas of Application for crowdsourcing: Crowd Science: Science is becoming increasingly collaborative There are research articles with thousands of collaborators There are even programs like Zooniverse Platform that engage non-scientists in science à Citizen Science Þ Take Aways: Crowds can create value by generating novel and diverse ideas and can also support organizations in selecting the right ideas Crowds reduce the organization’s local search bias Crowds need a guiding framework Digitalization and IT are powerful enablers of crowdsourcing Lecture 13: Opportunities and Risks of Digitalization in Commerce c