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Summary Principles 2 Track: Digital Firm
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This is a summary/notes of the lectures you get with Principles of Economics and Business with the track: Digital Firm. I passed this course with an 8 as final grade.
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Digital Firm TrackLecture 1 Part A: Dig Tech Impact on Productivity
Emphasis on impact of IT/AI on productivity.
Main discussion: IT/AI Productivity Paradox and impact of digital technologies on labor
Main concepts:
➢ Moore’s Law
➢ General purpose and single purpose technologies
➢ Complementarity between IT and organizational assets
➢ IT/AI productivity paradox
A Digital Firm is one in which nearly all of the organization’s significant business relationships
with consumers, suppliers and employees are digitally enabled and mediated
Digital Technologies and their impact: three lessons
1. We tend to overestimate the potential of new technologies in the short term but
underestimate it in the long run (Amara’s Law)
2. Digital technologies have unintended consequences
3. Smart technologies require smart organizations and smart people
A Digital Firm is one in which nearly all of the organization’s significant business relationships
with consumers, suppliers, and employees are digitally enabled and mediated. Core business
processes are accomplished through digital networks spanning the entire organization or
linking multiple organizations.
Digitization: the conversion of analog to digital. New (or improved) technology but same old
process.
Digitalization: it is the transition to become a digital business. This transition cannot succeed
unless organizational practices and processes and culture
Not all digital technologies will be adopted, depends on:
➢ Technological advancement
➢ Low prices
➢ Usefulness
➢ Easy to use
➢ And economic, political and societal choices
Labor productivity = output volume/ labor input use (total hours)
Impact ICT on labor input use:
➢ Substation of labor: automation
➢ Reducing coordination/transaction costs
Moore’s law???
,The Productivity Paradox
• During the 1980s services industries invested more than $ 1 trillion in Information
Technology. However productivity rose less than one percent.
• “There is no demonstrable correlation between the financial performance of a firm and
the amount it spends on Information Technology” (Strassmann, 1997)
• The benefits of computers are “the big lie of the information age” (Schrage, 1997)
Productivity Paradox solved but:
productivity growth 2nd industrial revolution strongly outperforms productivity growth digital
revolution (in size and length)
General Purpose Technologies
GPTs are technologies or clusters of related (complementary) innovations ‘characterized by
the potential for pervasive use in a wide range of sectors and by their technological dynamism’
(complementary innovations not necessarily technological).
They enable productivity improvements in multiple industries by automating or greatly
improving the efficiency of key production tasks such as the use of energy for work, or the
transfer and processing of information.
Steam engine, electricity and computers are GTPs
➢ Greatest increase in productivity historically with ‘general purpose technologies’
➢ This implies that productivity grows with clusters of innovation = combinatorial growth.
➢ This also means that there will be diffusion gaps: takes time before productivity reveals
in productivity statistics.
General Purpose Technologies and Combinatorial Growth
• GPT require complementary technologies to become productive
• ! Not only complementary technologies but also non-technological, organizational
complementarities
, Complementarity between IT- and Organizational Innovations
• Productivity gains vary huge across organizations and across countries:
the greatest benefits of ICT investments appear when they are accompanied with
complementary organizational innovations
o new skills (training people)
o new business processes (e.g. TQM, Lean Six Sigma, JIT, BPRE)
o new organizations
• For every dollar of IT there are several dollars ($ 9) of organizational investments that,
when combined, generate the large rise in measured firm productivity and value
(Brynjolfsson and Hitt, 1998) (Total Costs of Ownership, TCO).
• It may take 5-7 years before you see the impact on company level
Defining AI:
Artificial intelligence refers to principles and applications of computer algorithms that attempt
to mimic various aspects of human intelligence.
Why so much attention to AI recent years?
➢ Low prices & increase computer power (Moore’s Law)
➢ Rise of Big Data (data as the new oil)
➢ Technological advancement AI:
o From programmed
o To unprogrammed (self-learning)
Machine Learning
• Machine learning: computer algorithms that automatically
improve their competence through “experience” (mostly historical data).
• ML algorithms analyze these data in order to detect patterns or regularities that can be
extrapolated to future cases (learning).
• Given experience these machine-learning algorithms now automatically improve their
ability to speech, recommend on movies, songs, and all sorts of other information.
The Learning Machine
➢ Supervised: all data is labeled, and the algorithms learn to predict the output from the
input data.
➢ Unsupervised: all data is unlabeled, and the algorithms learn to inherent structure from
the input data.
➢ Reinforcement learning: learning takes place, based on feedback. No prior labels or
knowledge about good performance exists.
AI as General Purpose Technology
➢ It is spurring complementary innovations, e.g. redesign of cars
➢ It is (will become) pervasive: can be applied to many industries
➢ It is able to be improved over time
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