Digital Transformation Lecture 1

Study Notes

Wall Street sees significant potential in new digital businesses, compelling established firms to adapt.
Artificial intelligence (AI) is expected to cause broad societal impacts through rapid scientific advancements.
Harari's recommendations to manage AI progression include:
- Lifelong learning to keep up with changing demands.
- Creating test cases for future predictions.
- Developing an economic system to address job displacement caused by AI.

Digitization, digitalization, and digital transformation are defined in various ways, each emphasizing different aspects of technological change.

Strategies must evolve toward representation, connectivity, and aggregation.
Four key aspects of representation:
- Information conversion.
- Datafication of new information.
- Digital-to-physical transformation.
- Implementation of machine learning and algorithms.
Key shifts in connectivity include:
- Moving from one-to-one to many-to-many connections.
- Transitioning from on-demand to default connectivity.
- Emphasizing relevance over correctness in information.
Aggregation allows companies to combine previously disjoint data, offering:
- Enhanced understanding of organizational structures.
- More complex evaluations, such as credit scoring.
- Insights into individual customer needs, while posing risks of increased corporate surveillance and unethical data use.

Data is characterized by its scale-free nature, autogenic properties, fungibility, free replicability, and ability to be sold while retained.
Questions arise around data ownership, consent, access, and its reuse.
Leveraging connectivity and aggregation enhances a firm's scalability.

Four competitive processes leading to decline in incumbent firms:
- Internal dysfunction.
- Competitive rivalry.
- New market entrants (substitution).
- Commoditization of products/services.
Companies may retreat to niche markets in response to digital threats.
Disruptive innovations redefine customer value and business models across sectors.

Business ecosystems involve independent economic players collaboratively offering coherent solutions with distinct roles.
Ecosystem features differentiate them from traditional supply chains:
- Modularity, customization, multilaterism, and coordination.

Central shifts encompass:
- Connected vehicles.
- Autonomous technology (ranging from manual to fully automated).
- Shared mobility.
- Electric and sustainable energy vehicles.

Digital platforms risk commoditization and may prompt value inversion.
Platforms may transition across market segments (platform envelopment), exemplified by companies like Netflix.

It encompasses mechanization, automation, digitalization, and networking of industrial infrastructure.
Key trends include market internationalization, reduced production depth, decentralized control, mass customization, and open innovation.
The Solow Paradox suggests a disconnect between IT investment visibility and measurable economic effects, emphasizing complementary investments for value realization.

The exponential growth of data, with projections suggesting 5200 GB or 500 tons of books per human in 2020.
Data science focuses on extracting knowledge from vast, varied datasets through algorithms and technologies.
Knowledge is derived through deductive and inductive reasoning.
Knowledge Discovery in Data (KDD) involves data selection, cleaning, integration, and analysis, with three analysis types:
- Descriptive, explorative, and predictive analysis.

Traditional Customer Lifetime Value (CLV) metrics may overlook indirect customer value.
Customer value encompasses transaction revenues, attention, co-production, and network effects.
Current research promotes systems thinking, understanding inter-dependencies among customer groups.

Digital innovations disrupt existing models and introduce new business opportunities.
Pricing approaches include non-participative, participative, dynamic pricing, freemium models, and reverse pricing strategies to enhance customer experience and optimize revenue.

Same-side and cross-side network externalities are crucial for platforms.
The chicken-or-egg dilemma poses challenges, with strategies to overcome include leveraging existing user bases and creating value for key users.

Africa faces infrastructure deficits but has rapidly adopted mobile telephony for access to information and services.
Mobile banking has surged by nearly 200%.
ICT is identified to enhance economic development by improving market efficiency, managing supply chains, and facilitating service delivery, despite challenges from infrastructure and quality concerns.

Crowdsourcing harnesses external creativity through open calls and challenges.
Successful examples include Wikipedia and DARPA's initiatives.
Crowdsourcing can drive scientific collaboration, with platforms like Zooniverse engaging non-scientists in research.
Key takeaways highlight the necessity of a guiding framework and the enabling role of digitalization in crowdsourcing initiatives.