Leadership Challenges in Digital Transformation Globelics Academy, Tampere 16.8.2019 Matti Sommarberg
Leadership Challenges in Digital Transformation
Globelics Academy, Tampere 16.8.2019Matti Sommarberg
• Perspectives on discontinuities• Role of the technology• Empiric findings• Conclusions
Evolution vs. revolution
Foster, Richard N. (1986). Innovation: The Attacker’s Advantage, Summit Books, New York, USA, p.102
Perfo
rman
ce
Effort
Discontinuity
Utterback & Abernathy (1975). A Dynamic Model of Process and Product Innovation, Omega, Vol. 3, No.6, pp. 639-656
Discontinuity is often the target of innovation
It can also disrupt existing businesses or industries
Christensen, Clayton M. (2011 4th ed.). The Innovators Dilemma, HarperCollins, New York, USA, pp. xix
Time
Prod
uct P
erfo
rman
ce
Performance demanded at the low end of the market or in a new emerging segment
Performance demanded at the high end of the market
Progress due to disruptive
technologies
Progress due to sustaining
technologies
Which is not a feature from digital era
Utterback & Suarez (1993). Innovation, Competition and Industry Structure, Research Policy, Vol. 22, No.1, pp. 1-21
Some systemic innovation impact all industries
1780-1830 1830-1880 1880-1930 1930-1970 1970-2010
Nikolai Kondratiev 1892-1938
Dynamics has traditionally been driven by the value chain,
Michael E. Porter (1979), How Competitive Forces Shape Strategy, Harvard Business Review, Vol. 57, Issue 2, pp. 137-145
Rivalry among existing
competitors
Bargaining power of suppliers
Bargaining power of customers
Threat of new entrants
Threat of substitute products or services
Firm / Industry
Economic
Social
Technological
Ecological
Legal
Political
Modified from Aguilar, Francis Joseph (1967). Scanning the Business Environment, Collier-Macmillan, Toronto, Canada, pp. 1-17
as well business environment at large
or by the stakeholders.
Firm
Local Community
Owners
Consumer Advocates
Customers
Competitors
MediaEmployees
SIG
Environ mentalists
Suppliers
Governnents
Modified from Freeman, Edward, R. (2015). Strategic Management: A Stakeholder Approach, Cambridge University Press, Cambridge, UK, p. 25
Digital technologies drive industry convergence
Convergence: “the blurring of industry boundaries that creates competition among firms, which did not compete with another previously.”*
• ICT and media• Functional food• Consumer / industrial• Service into products• Software into everything
McKinsey Quarterly October 2017
* Prescott, J.E.; Karim S; Hsu S. (2014). The Strategic Process and Competitive Dynamics of Industry Convergence, Strategic Management Society, 34th Annual Conference, Madrid
and disruption cases are often out-of-industry (and they also shadow the actual phenomena)
Share economy Platform
Open Innovation Blockchain
13
Platforms are not explained by the value chain
Network effects
End-user knowledge
Open platforms
e.g. Alibaba
Innovation platforms
e.g. Apple Store
Trading platforms
e.g. Uber, AirBnB
Integration platforms
e.g. Santander “All in One Service”
Ailisto et al. (2016), Onko Suomi jäämässä alustatalouden junasta?, VNK 19/2016, p.18
Market pull(free competition from
customers)
Technology push(customer monopoly)
Two-way markets Multidirectional markets
Impact of digital technologies is difficult to detect as
Most digital technologies are generic
• Multiple applications• Across industries
Technologies are systemic and interrelated
Magnitude is also in our head
Availability HeuristicsKahneman, Daniel (2003). Maps of Bounded Rationality: Psychology of Behavioral Economics, American Economic Review, Vol. 93, Issue 5, pp. 1449-1475
Bounded RationalitySimon, Herbert A. (1979). Rational Decision Making in Business Organizations, American Economic Review, Vol. 69, Issue 4, pp. 493-513
Industry RecipeSpender J.-C. (1989), Industry Recipes, An Enquiry into Nature and Sources of Managerial Judgement, http://jcspender.com/uploads
Halo EffectRosenzweig, Phil (2007). The Halo Effect, Free Press, New York,
Absorptive CapacityCohen, Wesley M.; Levinthal, Daniel A. (1990). Absorptive Capacity: A New Perspective on Learning and Innovation, Administrative Science Quarterly, Vol. 35, Issue 1, pp. 128-152
Dominant LogicPrahalad, C.K.; Bettis, Richard A. (1986). The Dominant Logic: a New Linkage Between Diversity and Performance, Strategic Management Journal, Vol. 7, Issue 6, pp. 485-501
Status Quo BiasDaniel Kahneman; Jack, L. Knetsch; Richard H. Thaler (1991). Anomalies: The Endowment Effect, Loss Aversion, and Status Quo Bias, The Journal of Economic Perspectives, Vol. 5, Issue 1, pp. 193-206
AM / 3D printing
https://3dprinting.com/news/royal-navy-reveals-nautilus-100-3d-printed-submarine-concept/
• Decoupling physical value chain• New Features • Hybrid opportunities
• Material coverage ?• Cost development ?• New business models ?
https://www.worldmaritimenews.com
Big Data / Artificial Intelligence
Hans Morawec (2003), Robots, after all, Communications for ACM, Vol. 46, Issue 10, pp. 90-97
Moore
Cloud Computing
• Cost?• Capacity?• Security?• New business models?
• New normal already?
Internet of Things
0
5000
10000
15000
20000
25000
2016 2017 2018 2020
IoT installed base (millions of units)
Consumer Business (Cross-Industry)Business (Vertical)
8.4 Billion Connected "Things" Will Be in Use in 2017, Up 31 Percent From 2016, Gartner press release from February 7, 2017
• The development is inevitable• 5G?• Architecture?• Security?• New business models?
Model Based System Engineering
• Modelling capabilities• Multidisciplinary• Life time• Advanced design tools• Interfaces like AR, VR• Digital twin concept• Enabling co-creation
https://community.plm.automation.siemens.com/t5/Digital-Transformations/The-value-of-the-digital-twin/ba-p/385812?lightbox-message-images-385812=31800iB94D19235331E799
Robotics and/or autonomic systems
www.kalmarglobal.com
http://www.tut.fi/fi/tietoa-yliopistosta/uutiset-ja-tapahtumat/ robottibussit-liikenteeseen-hervannassa-x171216c3
https://waymo.com/
https://www.amazon.com
https://sanbot.com
https://www.rolls-royce.com/products-and-services/marine/ship-intelligence.aspx
What factors, enabled by digitalization, drive disruption in machine building industry serving the global container handling?
Does the view differ based on position in the value chain?
Continuous improvement Quantum leap Disruption
Products
Services
Operations
Business models
Nature of the potential impact
Staying where you are- This is housekeeping
Change of positions- Innovation gets you here
Change of rules- Transformation gets you here
Enabler Actor User
Decision-maker *
Synthesizer *
Scientist *
* Kuusi, Osmo (1999). Expertise In the Future Use of Generic Technologies, Epistemic and Methodological Considerations Concerning Delphi Studies, VATT-Research reports 59, Helsinki, pp. 36
• 246 research articles, books or reports
• 305 survey answers from 23 countries
• 60 interviews in 11 countries
• 3 industry cases
• Current business and ongoing experiments
https://tutcris.tut.fi/portal/en/publications/digitalization-as-a-paradigm-changer-in-machinebuilding-industry(9aecb1d2-dc64-4336-9c7e-44d7f27c3127).html
Digitalization impact
Survey
Drivers
Technology # 1 / 36 Mean
Big Data / AI 18 1.9Internet of Things 9 2.4Model Based System Engineering
5 3.9
Robotization 2 3.7AM / 3D 2 5.2Cloud computing 0 4.9
Economic Mean
Networks, crowds, platforms
13 2.2
Industry convergence 9 3.8Radical innovation 7 3.8Digital business models 4 2.7Firm, strategy and management
2 4.1
Industry forces (six) 1 5.2Risk capital 0 6.4
Delphi interviews
Big data, Artificial intelligence
18 / 361.9 / 1,3
- +
Delphi interviews
0 10 20 30 40 50
Prescriptive potential
Knowledge scalability
Users open their data
Advancement (e.g.cognitive computing)
Reduce of human errors
Emergence of platformtools
0 10 20 30 40 50
Lack of competences
Management beliefs
Data ownership conflictof interest
Data security risks
Data ownershipconfusion
Industry beliefs
13 /362,2 / 1,4
- +
Delphi interviews
0 10 20 30 40
Platform (industry)
Crowd intelligence effect
Platform (disipline)
Self-fulfillment motives ofknowledge workers
Unrestricted capacity
Fixed cost light
0 20 40 60
Management beliefs
Lack of capabilities(orchestration)
Legacy systems andprocesses
Lack of systems andprocesses
Conflict in IPR
Networks, crowds, platforms
Conclusions
Near-term
Long-term
1.Operational Efficiency• Asset utilization• Operational cost reduction• Worker productivity
2. New Products & Services• Pay-per-use• Software-based services• Data monetization
3. Outcome Economy• Pay-per-outcome• New connected ecosystems• Platform-enabled marketplace
4. Autonomous Pull Economy• Continuous demand-sensing• End-to-end automation• Resource optimization & waste reduction
World Economic Forum (2015). Industrial Internet of Things: Unleashing the Potential of Connected Products and Services
This appears still to make sense
Porter, Michael E.; Heppelman, James, E. (2014). How Smart, Connected Products Are Transforming Competition, Harvard Business Review, Vol. 92, Issue 11, pp. 64-88
Farm Equipment
System
Irrigation System
Seed Optimization
System
Weather Data
System
Farm Management
System
Weather mapsWeather forecasts
Weather data applicationRain, humidity, temperature sensors
Farm performance database
Seed database
Seed optimization application
Irrigation applicationField
sensorsIrrigation nodes
This already exists
CompetitorsCustomers
X
You You
Platforms come – like it or not
Suppliers
Anyone
Systemic productivity that has an impact to physical assets
Growth of underlying business activity
Is hardware growth sustainable?
M. Sommarberg, April 2014
Rogers, Everett M. (2003, 5th ed.) The Diffusion of Innovation, Free Press, New York, USA, p. 281
Early Adopters13.5 %
Early Majority34 %
Late Majority34 %
Laggards16 %
Innovators2.5 %
Diffusion of innovation still likely to matter
Degree of BigData AI Utilization
Datacompetencies
+
Efficiency ofoperations
Managementbeliefs
Industrybeliefs
Dominantlogic
Pressure toinvest
CapabilityInvestments
Amount ofdata
+Amount of IoT
sensors
Public data
+
Industryconvergence
Amount of relevanthistory data
+
Assets+
Advancement incognitive computing
Use cases
+
+Performingintelligence
New productfeatures
Advancedservices
New bizmodels
Domain intelligenceacquistion
Utilization ofplatforms
Orchestrationcapability
Disciplineintelligenceacquisition
Users opentheir data
Industryactivity
<Managementbeliefs>
Platformcapasity
Companyinteligence
Legacy
Platformsupply
Contributorsupply
Entrepreneurialknowledge workers
The impact is systemic
36
Public opinion (=Google trend)
Digitalization
Machine learningBig dataData analytics
37
Finnish experts and temporality
0,01,02,03,04,05,06,07,08,09,0
Products Service Operations Business models
Impact
2014 mean 2017 mean
0123456789
3D prin
ting
AI / Big da
taClou
d IoT
Industr
ial Inter
net
MBSE
Open In
novatio
n
Roboti
cs
Drivers
2014 mean 2017 mean
M. Baghai, S. Coley and D. White, The Alchemy of Growth, Texere Publishers, 2000. p. 5
Profit
Years
Horizon 1 – extend and defend core business
Horizon 3 – create viable options
Horizon 2 – build emerging businesses
Three strategic horizons
Temporality / Learning
Minzberg, Henry; Ahlstrand, Bruce; Lampel, Joseph (1998). Strategic Safari, The Free Press, New York, USA, p. 369
AM AI IoT PE OE OIProductsServicesOperations
Critical capabilities mapped, example
Spare part stock
becomes virtual
OEM decides technical
specification->
Higher standardization
AI can take care of 90 %
of the help desk
->Offshoring?
Are capability needs related to strategic ambition level (firm, industry, generic)?
• Business becomes data and user centric• Platforms decouple old value chains that transforms into networks• Speed of disruption is not slowed down by technology• Service of everything, outcome economy, systems of systems
disrupt current business models• View of impact is a strategic choice (strong polarization) • Leadership is vital (if transformation needed)• Capabilities and understanding -> Experiments -> Learning• Fundaments do not disappear (real world is still going be
analogical, domain knowledge)
• Co-Creation, between disciplines, systemic eco-systems, experiments -> long term PPP (including users when possible)
Conclusions
“Those who cannot change their minds cannot change anything”
- George Bernard Shaw