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©2019
Big Data en datagedreven waardecreatie:
Valt er nog iets te kiezen
Hét keten-event voor ondernemers in de maakindustrie
2 oktober 2019
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Prof. dr. J.F.M. (Frans) FeldbergProfessor of Data‐Driven Business InnovationSBE/Information, Logistics and Innovation
Research:• Data‐Driven Business Innovation• Economics of Artificial Intelligence• Business Intelligence/Business Analytics/Big Data• Online Decision Making (DSS & GDSS)• Mobile Sensing• Internet‐of‐Things
Business Consultant.
FransFeldberg
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1. Wat is er veranderd?2. Waarom zijn deze veranderingen belangrijk ?3. Hoe kunnen organisaties reageren, en waarde
creëren met data?
4. Inspireren.
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• Business Administration & Mathematics & Computer Sciences& ….• Bachelor and Master Business Analytics• Multidisciplinary Research Center• Eco System: Businesses & Science• One stop shop: Access to all relevant academic expertise
• Post Graduate Education: Business Analytics & Data Science (https://ee.sbe.vu.nl/nl/management/opleidingen/business‐analytics‐data‐science/inhoud/index.aspx/)
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CHANGEAHEAD
Wat has changed?
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BIG data
variety velocityvolume
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GranularUnmanageable
Renewal/UpdatingUnintentional
BIG data:
(Günther, Rezazade Mehrizi, Huysman, Feldberg, 2017)
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UNCERTAINTY AHEAD
Why important for organizations?
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DigitizedDemonetizedDematerializedDemocratizedDeceptiveDisruptive
(Diamandis, Kotler, 2015)
Data: Digital Innovation
(https://www.litterati.org)
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0,01 0,02 0,04 0,08 0,16 0,32 0,64 1,28 2,56 5,12 10,2
0 1 2 3 4 5 6 7 8 9 10
Deceptive
Moore’s LawDeceptive
Deceptive
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Andrew McAfee: When do we enter the second half of the chessboard?
1958 + 32 * 1,5 = 2006
US Bureau of Economic
Analysis starts tracking IT
Moore’s Law doubling period
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(https://nos.nl/artikel/2202863‐deze‐slimme‐pil‐houdt‐bij‐of‐je‐hem‐geslikt‐hebt.html)
Sensors with the size of sand grain……..
(www.nu.nl)
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Data: Waardecreatie?
Strength in numbers: How does data‐driven decision making affect firm performance?
(Brynjolfsson, E., Hitt, L. M., & Kim, H. H. , 2011).
Big Data en Waardecreatie: How do organizations create value from big data?
(Günther, W. A., Mehrizi, M. H. R., Huysman, M., & Feldberg, F., 2017).
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Work‐ Practice
Organizational
Supra‐Organizational
Centralized
Incremental
Decentralized
Radical
Inductive
Human
Deductive
Machine
Open
Economic
Controlled
Social
Gaining insights from big data for decision making.
Developing organizational designs and models.
Dealing with stakeholder interests.
How do organizations realize value from big data?(Debating big data: A literature review on realizing value from big data (Günther, Rezazade Mehrizi, Huysman & Feldberg, 2017))
https://www.sciencedirect.com/science/article/pii/S0963868717302615
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Characteristics (big) data:
Portability Interconnectivity
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Who will become the Uber of healthcare….?
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SOLUTIONS AHEAD
How can organizations create value with data?
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DATA‐DRIVEN BUSINESS MODEL INNOVATION
(Woerner & Wixom , 2015))
IMPROVE the business model
INNOVATE the business model
• New Data• New Insights• New Actions
• Data Monetization• Digital Transformation
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Improve: New Data
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Improve: New Insights
Article 8 EU Energy Efficiency Directive (energie efficientie richtlijn)- Requires large enterprises to comply with the energy audit obligation –
EED energie audit onderdelen:
1. Schematisch overzicht van alle energiestromen incl. vervoer
2. Beschrijving belangrijkste factoren die energieverbruik beïnvloeden
3. Gekwantificeerd overzicht van het energiebesparingspotentieel van de onderneming voor de komende 4 jaar
4. Beschrijving mogelijke kosteneffectieve besparingsmaatregelen
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Improve: Actions
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DATA‐DRIVEN BUSINESS MODEL INNOVATION
(Woerner & Wixom , 2015))
IMPROVE the business model
INNOVATE the business model
• New Data• New Insights• New Actions
• Data Monetization• Digital Transformation
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Innovate: Data Monetization
Selling
BarteringWrapping
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AirClean&Mean
Circular
Solar
FinancialServicesValue:
clean wash, lowest costs, lowest environmental impact.
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KEY PARTNERS KEY ACTIVITIES VALUE PROPOSITION
CUSTOMERRELATIONSHIPS
CUSTOMERSEGMENTS
KEY RESOURCES
DISTRIBUTION CHANNELS
COST STRUCTURE REVENUE STREAMS
(Osterwalder, A., & Pigneur, Y. , 2010)
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Innovate: Digital Transformation
Portability Interconnectivity
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Digital Twins
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Bouwwereld.nl
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Innovate: Digital Transformation
Digital Asset Management
Time Based ‐> Condition Based
(Prediction Machine: Predictive Maintenance)
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What is the best infrastructure for me?
What is the best education for me?
What is the best treatment for me?
What is the best judge for me?
What is the best care for me?
What is the best product service for me?
What is the best asset (management) for me?
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KEY PARTNERS KEY ACTIVITIES VALUE PROPOSITION
CUSTOMERRELATIONSHIPS
CUSTOMERSEGMENTS
KEY RESOURCES
DISTRIBUTION CHANNELS
COST STRUCTURE REVENUE STREAMS
(Osterwalder, A., & Pigneur, Y. , 2010)
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“What are we going to do with the ‘new thing’”,
must be changed in:
“How are we going to change the old idea”!
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Challenges, Risks:
•Data Privacy and Ethics: BIG Dilemma’s!
•Data Obsession (“the dictatorship of data”)
•Data Quality: new paradigms?
•Skills: Data Scientists
•Energy
•Security
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JOURNEY
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Field Lab Smart Maintenance Techport
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Datagedreven waardecreatie:Valt er nog iets te kiezen?
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The world’s largest taxi company owns no taxis….
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Who will become the of your industry..?
55
If you want to know more about the economics of artificial intelligence, prediction machines, and how AI can help to solve complex problems (link to SDGs), check: https://youtu.be/p7XwKKTLRlw
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