Digital Transformation Strategy - summaries papers
Lecture 1 - Adner et al. (2019): What is different about digital strategy? From quantitative
to qualitative change 1
Lecture 1 - Nambisan et al. (2019): The digital transformation of innovation and
entrepreneurship: progress, challenges and key themes 4
Lecture 1 - Verhoef et al. (2021): Digital transformation: a multidisciplinary reflection and
research agenda 6
Lecture 2 - Cennamo & Santalo (2013): Platform competition: strategic trade-offs in
platform markets 10
Lecture 2 - Zhu & Iansiti (2012): Entry into platform-based markets 14
Lecture 3 - Goldsby & Hanisch (2022): The boon and bane of blockchain: getting the
governance right 16
Lecture 3 - Lumineau et al., (2021): Blockchain governance - A new way of organizing
collaborations? 21
Lecture 4 - McAfee & Brynjolfsson (2012): Big data: the management revolution 27
Lecture 4 - Davenport (2006): Competing on analytics 29
Lecture 4 - Chen, Chiang and Storey (2012): Business intelligence and analytics: from big
data to big impact 31
Lecture 5 - Argawal et al. (2019): Prediction, Judgment, and Complexity: A theory of
decision-making and Artificial Intelligence 34
Lecture 5 - Berente et al. (2021): Managing artificial intelligence 36
Lecture 5 - Dixon et al. (2021): The robot revolution: managerial and employment
consequences for firms → notes from lecture 5 38
Lecture 6 - Tirole (2022): Competition and the industrial challenge for the digital age? 39
Lecture 6 - Parker et al. (2020): Digital platforms and antitrust 41
Lecture 6 - Martens (2018): The impact of data access regimes on artificial intelligence
and machine learning 45
,Lecture 1 - Adner et al. (2019): What is different about digital strategy?
From quantitative to qualitative change
Digital foundations
There are 3 foundational processes that explain much of the variety of phenomena that are
subsumed under the digital transformation: (1) representation, (2) connectivity, (3) aggregation
1. Representation
- Digital transformation begins with digitization. It is the digital representation of
information that enables analysis and algorithmic manipulation
- Quantitative acceleration = when digital signals are transformed into analog actions
2. Connectivity
- Digitization creates new connections and enhances existing connections among objects,
individuals and organizations. There is a huge amount of potential connections. The
quantitative explosion of connected points has enabled the emergence of complete new
business and organizational models
- But the shift to more connectivity is not just because of the increase in network density.
As products and services become more digitized, every product or service can be used
to facilitate connections
3. Aggregation
- Beyond the quantitative growth in data storage capacity and reduction in storage costs
there is a third qualitative shift (= arises from the ability to combine previously disjoint
data to answer questions that were formerly impossible to address) → data aggregation.
- Example: combining multiple types of data on an individual to say something about their
health risks
Interactions
Each of these effects of digitization is significant but truly dramatic changes become visible
when they interact and reinforce each other.
- A combination of enhanced connectivity and data aggregation produces new
functionalities and opportunities for value creation and capture
- There are also strong complementarities between the processes; development of the
one increases the value of the other:
- Aggregation enables potentially better connectivity
- More connectivity produces data that can benefit from being aggregated
- As connectivity and aggregation erode transaction costs (and in turn accelerate as
transaction costs erode), the resulting increase in transactions enhances the potential for
new and more kinds of data. Consequently, advances in data representation become
ever more valuable in the effort to process these data and mitigate the constraints of
human-bounded rationality.
1
, - This spurs further investments in connectivity and aggregation, driving a positive
feedback loop
Implications
What do these transformative processes underlying digitization mean for firm strategy and
strategy research?
1. Resource-based View (RBV): data and algorithms as self-generating resources
- Resources can be scale-free (non rivalrous, e.g. a brand) and non scale-free (e.g. cash).
Data is a scale-free resource and can be used for competitive advantage
- New form of digital data creation: autogenic = when the very act of engaging with data
creates new data; self-creating data
- Fungibility (= vervangbaarheid) van data: smaller decline in value indicates higher
fungibility
2. Data, ownership and factor markets: who should own the data?
- With enhanced connectivity it is no longer easy to curtail information flow at the legal
boundaries of the firm → new challenges around protection of IP and sensitive
information
- As the combination of autogenesis, scalability and fungibility becomes more common,
we expect greater variety in solutions to challenges this potentially creates
3. Digitization, replication, and super-scalable business models
- Scalability can improve significantly when this property interacts with connectivity
- Aggregation can also enhance connectivity to improve firm scalability. As you
accumulate more data from each user, the product becomes more intelligent and attracts
more users, enjoys higher scalability; positive feedback loop
4. Digital transformation of firm scope
- The potential fungibility of the digital assets that firms accumulate can create
opportunities in multiple markets. As these capabilities are increasingly being leveraged
to enter new markets, industry boundaries are becoming more blurred. This implies that
firms are increasingly likely to face competition from firms outside their industries and
that the nature of their competitive response can shift.
- Many digital firms also expand their businesses into the territories of their value-creation
partners as they grow
- In the digital-enabled contexts more potential for synergies appear.
5. Digital transformation and the internal organization of firms
- Hierarchical control (of large-scale organizations) may be improvable through digital
transformation. The connectivity implied that managers lose their monopoly on
information
2
, 6. Organizational sensemaking in an algorithmic world
- Algorithmic extraction of actionable predictions has become a powerful new form of data
representation.
- Managers need to consider a delicate balance between letting go of the need to
understand in order to predict data.
Conclusion
- A new set of frameworks may be useful to understand the impact of digital
transformation. Don’t be too focused on the individual components of digital technologies
(e.g. data, algorithms), you may mask the quantitative changes that arise at the level of
these processes that involve multiple components
- The impact of these 3 processes have witnessed qualitative changes: representation,
connectivity and aggregation
3
Lecture 1 - Adner et al. (2019): What is different about digital strategy? From quantitative
to qualitative change 1
Lecture 1 - Nambisan et al. (2019): The digital transformation of innovation and
entrepreneurship: progress, challenges and key themes 4
Lecture 1 - Verhoef et al. (2021): Digital transformation: a multidisciplinary reflection and
research agenda 6
Lecture 2 - Cennamo & Santalo (2013): Platform competition: strategic trade-offs in
platform markets 10
Lecture 2 - Zhu & Iansiti (2012): Entry into platform-based markets 14
Lecture 3 - Goldsby & Hanisch (2022): The boon and bane of blockchain: getting the
governance right 16
Lecture 3 - Lumineau et al., (2021): Blockchain governance - A new way of organizing
collaborations? 21
Lecture 4 - McAfee & Brynjolfsson (2012): Big data: the management revolution 27
Lecture 4 - Davenport (2006): Competing on analytics 29
Lecture 4 - Chen, Chiang and Storey (2012): Business intelligence and analytics: from big
data to big impact 31
Lecture 5 - Argawal et al. (2019): Prediction, Judgment, and Complexity: A theory of
decision-making and Artificial Intelligence 34
Lecture 5 - Berente et al. (2021): Managing artificial intelligence 36
Lecture 5 - Dixon et al. (2021): The robot revolution: managerial and employment
consequences for firms → notes from lecture 5 38
Lecture 6 - Tirole (2022): Competition and the industrial challenge for the digital age? 39
Lecture 6 - Parker et al. (2020): Digital platforms and antitrust 41
Lecture 6 - Martens (2018): The impact of data access regimes on artificial intelligence
and machine learning 45
,Lecture 1 - Adner et al. (2019): What is different about digital strategy?
From quantitative to qualitative change
Digital foundations
There are 3 foundational processes that explain much of the variety of phenomena that are
subsumed under the digital transformation: (1) representation, (2) connectivity, (3) aggregation
1. Representation
- Digital transformation begins with digitization. It is the digital representation of
information that enables analysis and algorithmic manipulation
- Quantitative acceleration = when digital signals are transformed into analog actions
2. Connectivity
- Digitization creates new connections and enhances existing connections among objects,
individuals and organizations. There is a huge amount of potential connections. The
quantitative explosion of connected points has enabled the emergence of complete new
business and organizational models
- But the shift to more connectivity is not just because of the increase in network density.
As products and services become more digitized, every product or service can be used
to facilitate connections
3. Aggregation
- Beyond the quantitative growth in data storage capacity and reduction in storage costs
there is a third qualitative shift (= arises from the ability to combine previously disjoint
data to answer questions that were formerly impossible to address) → data aggregation.
- Example: combining multiple types of data on an individual to say something about their
health risks
Interactions
Each of these effects of digitization is significant but truly dramatic changes become visible
when they interact and reinforce each other.
- A combination of enhanced connectivity and data aggregation produces new
functionalities and opportunities for value creation and capture
- There are also strong complementarities between the processes; development of the
one increases the value of the other:
- Aggregation enables potentially better connectivity
- More connectivity produces data that can benefit from being aggregated
- As connectivity and aggregation erode transaction costs (and in turn accelerate as
transaction costs erode), the resulting increase in transactions enhances the potential for
new and more kinds of data. Consequently, advances in data representation become
ever more valuable in the effort to process these data and mitigate the constraints of
human-bounded rationality.
1
, - This spurs further investments in connectivity and aggregation, driving a positive
feedback loop
Implications
What do these transformative processes underlying digitization mean for firm strategy and
strategy research?
1. Resource-based View (RBV): data and algorithms as self-generating resources
- Resources can be scale-free (non rivalrous, e.g. a brand) and non scale-free (e.g. cash).
Data is a scale-free resource and can be used for competitive advantage
- New form of digital data creation: autogenic = when the very act of engaging with data
creates new data; self-creating data
- Fungibility (= vervangbaarheid) van data: smaller decline in value indicates higher
fungibility
2. Data, ownership and factor markets: who should own the data?
- With enhanced connectivity it is no longer easy to curtail information flow at the legal
boundaries of the firm → new challenges around protection of IP and sensitive
information
- As the combination of autogenesis, scalability and fungibility becomes more common,
we expect greater variety in solutions to challenges this potentially creates
3. Digitization, replication, and super-scalable business models
- Scalability can improve significantly when this property interacts with connectivity
- Aggregation can also enhance connectivity to improve firm scalability. As you
accumulate more data from each user, the product becomes more intelligent and attracts
more users, enjoys higher scalability; positive feedback loop
4. Digital transformation of firm scope
- The potential fungibility of the digital assets that firms accumulate can create
opportunities in multiple markets. As these capabilities are increasingly being leveraged
to enter new markets, industry boundaries are becoming more blurred. This implies that
firms are increasingly likely to face competition from firms outside their industries and
that the nature of their competitive response can shift.
- Many digital firms also expand their businesses into the territories of their value-creation
partners as they grow
- In the digital-enabled contexts more potential for synergies appear.
5. Digital transformation and the internal organization of firms
- Hierarchical control (of large-scale organizations) may be improvable through digital
transformation. The connectivity implied that managers lose their monopoly on
information
2
, 6. Organizational sensemaking in an algorithmic world
- Algorithmic extraction of actionable predictions has become a powerful new form of data
representation.
- Managers need to consider a delicate balance between letting go of the need to
understand in order to predict data.
Conclusion
- A new set of frameworks may be useful to understand the impact of digital
transformation. Don’t be too focused on the individual components of digital technologies
(e.g. data, algorithms), you may mask the quantitative changes that arise at the level of
these processes that involve multiple components
- The impact of these 3 processes have witnessed qualitative changes: representation,
connectivity and aggregation
3
