Week 1: Introduction/Digital Business Strategy
Carr (2003) Bharadwaj et al. (2013)
IT doesn't matter Digital Business Strategy: Toward a Next Generation of Insights
Main assertion is that IT is diminishing Four key
as a source of strategic differentiation themes
important distinction: proprietary vs
infrastructural technologies
"It is an infrastucrual technology" --> comoditization
New rules for IT management:
Spend less; Follow, don't lead;
Focus on vulnerabilities, not opportunities
Fichman (2014) Ross, Beath & Sebastian (2017) McKinsey & Company Schrage, Muttreja & Kwan (2022)
Distinctive IT Characteristics: (2021)
How to develop a Great Digital Strategy How the wrong KPI's doom Dig. Trans.
Implications for Digital Innovation and
A great digital strategy provides Executives must KPI's should lead, not track
Value Creation
1) Moore's Law direction, enabling executives to lead consider 3 4-component leadership framework
2) Digitalization (has lead to convergence)
digital initiatives, gauge their progress, components when for KPI-driven Dig. Transform.
3) Network Effects and then redirect those efforts as investing: 1. Create a strategic KPI portfolio
4) Switching Costs needed. 1. Scale of Impact 2. Commit to data as a digital asset
Customer Engagement Strategies 2. Technical Maturity 3. Orchestrate data flows to make
Transformational Digitized Solutions Strategies 3. Fit with the org. KPI's sharable, visible, and dymamic
Choose Only One Strategy See paper for trends 4. Commit to continuous KPI impro-
Build an Operational Backbone vement
Summary Impact Chain of Influences Leading to an Transformational Impact
Industry Moore’s Law & Digitalization à device and network convergence à destruction of tight couplings between
transformation service modes and underlying technologies à industry and market convergence; radical transformation of
whole industries
Distinctive diffusion Network effects à “critical mass” diffusion dynamics, path dependency, winner takes all, lock-in à standard
dynamics wars, risk of stranding
More diverse Moore’s Law & Digitalization à widespread diffusion of cheap digital infrastructures à increase ability to
products and aggregate product on demand through online channels + increased ability of consumers to find niche products
services suited to their tastes à greater diversity of products and services developed and offered (“Long Tail” effect).
More personalized Digitalization à reprogrammability, memorability, associability à greater personalization of novel processes,
products and products and services
services
Faster innovation Moore’s Law & Digitalization à dramatically lowered cost/increased ease of experimentation + complimentary
cycles and changes to innovation processes, structures, incentives à more rapid development and evolution of
processes innovative processes and products
Faster/broader Moore’s Law & Digitalization à rapid price/performance improvement of physical digital products; near-zero
product diffusion cost of duplication and distribution of improvements for pure information products à accelerated emergence
and faster/broader diffusion of new products and business models
Product pricing and Digitalization à near zero cost of duplication and distribution; digital rights management à intellectual
delivery flexibility property threats; increased control over how digital products are used, when and by whom (e.g., bundling,
trials, “freemium” models); greater pricing flexibility (e.g., how much is charged, to whom, when, by what
mechanism, and for what level of functionality)
New ways to Moore’s Law & Digitalization & Network Effects à widespread diffusion of cheap digital infrastructures à
market new new avenues for marketing and supporting new products (e.g., sponsored search and context-based ads,
products social media, marketing/online word-of-mouth)
Move to smart Moore’s Law & Digitalization & Network Effects à increased feasibility of embedding digital sensors and
technologies and processors in a wide range of everyday items and then connecting them up into an “Internet of Things” à
servitization widespread emergence of “smart” technologies; accelerated move to servitization (converting products into
services) and other kinds of new business models enabled by smart technologies
Move to real-time Moore’s Law & Digitalization à feasibility of understanding natural language questions and rapidly searching
question-answering and then extracting knowledge from huge troves of unstructured data à new organizational processes and
systems business models based on generalized real-time question-answering systems
Creation of Digitalization à information processes as they are automated à automatic capture of vast new stores of
analytics-driven detailed data about processes à pervasive opportunities for analysis of all technology-mediated processes à
digital innovation increased opportunities for process and product/business model innovation
opportunities
Democratized Moore’s Law & Digitalization à widespread diffusion of cheap digital infrastructures à increased ease of
innovation distributed collaboration and peer production à process and product innovation discovery and development
becomes more open, democratized, and user-driven.
, Creation of Digitalization à information processes as they are automated à automatic capture of vast new stores of
analytics-driven detailed data about processes à pervasive opportunities for analysis of all technology-mediated processes à
digital innovation increased opportunities for process and product/business model innovation
opportunities
Democratized Moore’s Law & Digitalization à widespread diffusion of cheap digital infrastructures à increased ease of
innovation distributed collaboration and peer production à process and product innovation discovery and development
becomes more open, democratized, and user-driven.
Week 2: Technology-centric view of IT; ERP; IOS; Platfoms
Dhar & Sundararajan (2007): Blueprint of IT in
Business
The three consequences of these invariants describe a technology-centric view
of thinking about IT and its consequences for business and society
Davenport (1998)
Putting the Enterprise into the Enterprise System (ES)
- An Enterprise System (ES) enables a company to
integrate the data used throughout its entire organization
- Configuration Mechanism: Modules and Configuration Tables
- ES have a direct, and often paradoxical, impact Johnston & Vitale (1998)
- Those companies that stressed the enterprise , not the Creating Competitive Advantage with Interorganizational Systems (IOS)
system, gained the greatest benefits. - Classification: business purpose of the system, relationship between the
sponsoring organization and the other participants, and on the information
function in the system
Rangathan & Brown (2016)
ERP Investments and the Market Value of Firms Jernigan et al. (2016)
Towards an Understanding of influential ERP Project Variables Data Sharing and Analytics are Driving Success with IoT
- Functional Scope + Markt value - Data sharing correlates with the ability to analyze data
- Physical Scope + Market Value - 3 Issues: 3 issues: scaling, public reaction, safeguarding data
- Vendor Status did not yield higher returns to firms - 3 ways to get value:
Organizational Integration (OI) is the extend to which 1) Analytics Capabilities Are Key 2)Embrace Complexity
distinct and interdependent components constitute a 3)IoT not enough to differentiate
whole. 2 kinds of OI with ERP: Technical Integration and - 3 Takeaways: 1) Analytics capability 2) Prepare to share
Business Integration 3) Prepare the customer/market
Alstyne, Parker & Choudary (2016)
Pipelines, Platforms, and the New Rules of Strategy
Pipeline: simple value chain model: output is worth
More than the input = value creation
Platform: network effects = value creation
5 forces of Porter apply to Platforms
Three key shifts in moving from a pipeline to a platform
1) resource control --> resource orchestration
2) internal optimization --> external interaction
3) focus on customer value --> focus on ecosystem value
