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How are big data and analytics shaping strategyand management?
Henri Schildt
Professor of Strategy
Aalto University
9.3.2017
Some questions I have been working on
March 13, 2017 © Aalto University Executive Education 2
What is actually novel in the contemporary "digitalization" that companies now allegedly face?
How does big data influence organization and management in companies?
How does big data influence firm strategies and their sources of competitive advantage?
Digitalization ≈ Data
March 13, 2017 © Aalto University Executive Education 3
run and optimize
business processes
do business and
secure profitsorganize and manage
Data has significant implications how corporations...
Software is eating the world- Marc Andreessen
Biggest changes in technology costs & increasing human skills
• Cost of analytics is less than10% of what it was 15 years ago
– Creating coherent and clean datasets remains a hurdle
• Talent remains scarce, but skills are steadily diffusing
– McKinsey estimates shortage of nearly 200 000 analysts and 1.5 million
analytics-proficient managers by 2020 in the United States
March 13, 2017 © Aalto University Executive Education 5
Kinds of data analytics
March 13, 2017 © Aalto University Executive Education 6
Operational Tactical Strategic
Descriptive
(reports)
Predictive
(forecasting)
Prescriptive
(tied to actions)
1
2
3
Who are our most
important customers
and how should we
serve them?
Where should
we open our
next store?
How much should
we pay to show an
ad for this user?
The source of this categorization is unclear,
the schematic has been widely used, incl.
Gartner’s reports.
How does data change how companies organize?
March 13, 2017 © Aalto University Executive Education 7
Dreams of omniscience
March 13, 2017 © Aalto University Executive Education 8
Measuring processes
and performance
Controlling
processes with data
Reducing the required
workforce
Few simple measures for
outputs
Rich digital representations
of key inputs and outputs
Smart aggregate metrics
Experienced managers
supervise processes
Digital control of tasks
Automated feedback
Key decisions made by
algorithms
Learning drives greater
employee productivity
Robots & software robots
Micro-outsourcing
Self-service design
Myopic and reactive company
Holistic and proactive company
See e.g.: Winig, L. 2016. “GE’ s Big Bet on Data and Analytics,” MIT Sloan Management Review.
Optimizing is inherently different from learning
March 13, 2017 © Aalto University Executive Education 9
The optimizing organization?
March 13, 2017 © Aalto University Executive Education 10
The learning organization The optimizing organization
Source of
advantage
Ability to gain, create, and
distribute knowledge
Ability to coordinate and make
optimal choices through
superior data and with scale
Central
challenges
Knowledge leakage,
learning traps, myopia
Lack of accurate and timely
data, optimizing the wrong
things
Design of work
roles
Rich jobs that create
opportunities for continuous
learning
Simple predictable and fixed
jobs suitable for algorithmic
control
Role of IT IT as tool used by skilled
humans
IT uses humans to achieve its
goals
Algorithmic management
• Complex real-time data on
employees enables supervision and
control through algorithms
– Employees no longer need human
managers
– Alternatively, individual managers can
have dozens of subordinates
• This has obvious economic benefits
• Equally obvious human costs
March 13, 2017 © Aalto University Executive Education 11
Sources: Lee, M. K., Kusbit, D., Metsky, E., & Dabbish, L. (2015). Working with machines: The impact of
algorithmic and data-driven management on human workers. Proceedings of the 33rd Annual ACM
Conference on Human Factors in Computing Systems. 1603–1612. Seoul, Republic of Korea: ACM.
Schildt,H. (2017). Big data and organizational design – the brave new world of algorithmic management and
computer augmented transparency, Innovation: Organization and Management, 19:1, 23-30.
Becoming data-driven is a cultural challenge, not just technological
Many firms follow HiPPOs (Highest Paid Person’s Opinions)
March 13, 2017 © Aalto University Executive Education 12HiPPO was popularized by McAfee & Brynjolfsson HBR article in 2012, but it has
older history dating at least to Avinash Kaushik blog in 2006.
Culture of secrecy
March 13, 2017 © Aalto University Executive Education 13See also: Grey & Costas book Secrecy at Work (2016) and their related article
(Costas & Grey, 2014. "Bringing secrecy into the open”. Organization Studies)
Culture of secrecy Culture of transparency
Knowledge is a valuable asset that
must be guarded
Speed and agility are vital and require
openness
Managers should not poke their
noses in other departments’ issues;
division of labor creates efficiency
Issues are not tied to departments;
customer and shareholder value
concerns everyone
Privacy is best dealt with by limiting
access to data
Everyone must respect privacy; misuse
dealt with retrospectively
Communications support
management perspective and
alignment around strategy
We cannot control employee
interpretations of data; dissenting views
are valuable
How does data change strategies and the sources of competitive advantage?
March 13, 2017 © Aalto University Executive Education 14
Managers are increasing looking towards business model innovation for growth
March 13, 2017 © Aalto University Executive Education 15
Process
innovation
(1800->)
Product
innovation
(1920->)
Business
model
innovation
Data changes business models
March 13, 2017 © Aalto University Executive Education 16
Customizable
products
Service delivery
through digital
channels
If the supplier gets
data ownership,
relationships are
longer, otherwise
shorter
Freemium models and
multi-sided platforms
Digital allows low variable
costs and rewards models
with high fixed costs
Partnering is
more crucial
for
combining
data and
monetization
Data and
customer
relationships are
central assets
Move from products to services
and solutions
Multi-sided business models and platform ecosystems
• Data-centric operations drive firms to cater for multiple
markets and become “information intermediaries”
– Low price, extremely low variable costs
– Long-term relationships to drive down cost of sales
March 13, 2017 © Aalto University Executive Education 17
See: Thomas, L.D.W., Autio, E., & Gann, D.M. 2014. Architectual leverage: putting
platforms in context. Academy of Management Perspectives, 28: 198-219.
Platform business models center around focused service with scale
• Storage and order fulfillment as a web-based service to clients
– “Amazon is a gigantic peripheral you can plug into your IT system”
(Amazon CEO Jeff Bezos in a letter to shareholders)
March 13, 2017 © Aalto University Executive Education 18
API economy?
• Application Programming Interfaces
– Simple mechanisms through which services can be requested and
delivered inside and across firms
• Practitioners (e.g. IBM) see transformative potential
– More efficient transactions
– Lacking gatekeepers, fosters innovation
• Implications for strategy and industry evolution have not really been
examined thus far in the literature; it would seem that…
– Global firms provide cheap scalable services through APIs
– Local companies combine the services into customer-oriented solutions
March 13, 2017 © Aalto University Executive Education 19
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