isde big data 20140910
DESCRIPTION
BigDataTRANSCRIPT
Innovation and Strategy in
the Digital Economy
Class 2: Data and “Big Data” in Business
Milan Miric – CBS / INO
About me
● PhD Student at Department of Innovation & Organizational Economics.
● Area of expertise: – Digital economy, technology platforms, innovation, competitive strategy &
commercialization.
● Academic background: – Undergraduate degree in Mechanical Engineering, MBA.
● Visiting scholar at Bocconi University (2012 – 2013) and London Business School (2013 – 2015).
Positioning of this class
● Class 1: Digital transformation
– Focus: Digital technology is transforming business.
● Class 2: Data & “Big Data”
– Focus: How is “Big Data” specifically is shaping business.
Digital Transformation: Recap
Digital technology transforming a wide number of industries.
● Affecting the way firms do business in brick-and-mortar industries.
● Creating new types of competitors for firms in digital industries.
● Creating entirely new industries that did not previously exist.
Brynjolfsson & Hitt (1996)
Brynjolfsson & Hitt (1996)
Digital transformation & Data● Digital vs. Analog Technology:
– Analog: Information represented by electronic pulses.
– Digital: Information represented by binary (0 or 1) values.
Key distinction: Digital information is easier to collect, store, analyze & less noisy (prone to errors).
So far more data is being collected than ever before!
From Varian (2013)
● A billion hours ago, modern homo sapiens emerged.
● A billion minutes ago, Christianity began.
● A billion seconds ago, the IBM PC was released.
● A billion Google searches ago … was this morning.
Benefits of Data Explosion
● Scope for production efficiencies.
– Ex. Automobile manufacturers.
● Scope for more effective marketing.
– Ex. Airline / Hotel rewards programs.
● Scope to collect, combine and analyze information which was previously not possible.
– Ex. Demographics – behavior - location – revealed preferences.
Challenges of Data Explosion
● Challenges of collecting data.
– Ex. Collecting millions of data points in real time.
● Challenge of storing and managing data.
– Ex. Storing vast amounts of relational information.
● Challenge of analyzing data.
– Ex. Difficult to disentangle causal effects.
– Ex. Difficult to analyze data with such a large amounts of variables / observations.
In this session
● What is the data used for?
● What makes data a valuable asset?
● (How) can firms profit from data?
Hype around
BIG data!
But does this answer the
earlier questions?
NO!
What is data used for?
Data in Brick-and-Mortar Industries
● Firms use data to offer better products and services.
● Winners & Losers:
– What are examples of firms that are doing this well? (AND WHY?)
– What are examples of firms that are doing this poorly (AND WHY?)
● In products? In services? In manufacturing?
● Can “data” be a source of competitive advantage? Why or why not?
Data in Digital Industries
Firms use data to offer better products and services.
● Winners & Losers:
– What are examples of firms that are doing this well? (AND WHY?)
– What are examples of firms that are doing this poorly (AND WHY?)
● In products? In services?
– Can “data” be a source of competitive advantage for digital businesses? Why or why not?
From Chen et al. (2012)
From Chen et al. (2012)
Break
(15 min.)
What is Data Used for?
● Inform decision making?
(evidence based decision making)
● Improve productivity.
● Offer new products / services.
But, What makes data valuable?
What type of data is valuable here?(Examples)
● Inform decision making? (evidence based decision making)
● Improve productivity.
● Offer new products / services.
What is the abstract “value” of data?
How is the value of data measured?
Scientific Question:
How would you measure the actual value of data?(as precisely as possible)
Avg. Revenue Per User: Facebook, Twitter, Google
Does this reflect the market value of data?
Then, can firms profit (develop CA) from
data?
What is nessesary for data to provide CA?
● Valuable.
● Rare (Not everybody has it).
● Inimitable (Difficult to copy).
● Organization Specific
(More valuable to own it than sell it).
CA from Data
Firms can have an advantage over competitors based on data.
● Winners & Losers:
– What are examples of firms that are doing this well?
– What are examples of firms that are doing this poorly?
What are examples of firms that may be better off selling their data than profiting from it themselves.
What does a market for data look like?
Break
(15 min.)
How does the revenue from users translate into valuations?
Source: Forbes 2013.
What explains the size of these valuations?
For example:
Why was WhatsApp valued at $19 Bn?