Data driven business models for Manufacturing Companies

1. Data driven business models for
Manufacturing Companies
Karan Menon
7th September 2021
Johtajuussymposium 2021
Tampere University

2. About Me
Dr. Karan Menon
 Bachelor’s in Chemical Engineering (2007), Sardar Patel University, India
 Master’s in Material Science (2011), Tampere University of Technology, Finland
 PhD (tech.) (2020), Tampere University, Finland – Title - Industrial internet enabled value creation for
manufacturing companies
 Project Manager for Business Finland Projects– SNOBI & Future Spaces
 Topics: Industrial Internet, Industry 4.0, Business Models, Platforms, Business Data Analytics, Digital
Transformation in Industry
 Research Partner Network: West Virginia University (USA), University of St. Gallen (Switzerland),
Kristiania University College (Norway) Copenhagen Business School (Denmark), Manufacturing
companies in Finland, Germany and USA
Email– karan.menon@tuni.fi
Twitter - @menonkaran
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Karan Menon

3. About Us
Unit of Information and Knowledge Management, Faculty of Management and Business, Tampere University
Novel Business Models research group –
• Professor Hannu Kärkkäinen
• Dr. Karan Menon (Project Manager)
• Dr. Prasanna Kukkamalla (Post-Doctoral Researcher)
• Dr. Sameer Mittal (Post-Doctoral Researcher)
• MSc. Mikko Uuskoski (Doctoral Student)
• MSc. Olli Kuismanen (Doctoral Student)
• MSc. Veli-Matti Uski (Doctoral Student)
• MSc. Jayesh Gupta (Doctoral Student)
• Mr. Joonas Schroderus (Project Researcher)
Overall expertise in – Data based value creation, Organizational transformation, Novel business models (design and
implementation), Maturity models, roadmapping, Knowledge management, Information management
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4. Agenda
 Technology enables new business models
 Evolution of the Business Models
 Data driven novel business models
 SME perspective
 Implementation tools
 Case example
 Conclusions and takeaways
 What are we doing on this topic?
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5. What is Internet of Things for us?
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Karan Menon
Reference: https://www.apple.com/watch/ &
https://www.apple.com/watch/why-apple-watch/

6. What is Industrial Internet of Things?
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Karan Menon
https://www.i-scoop.eu/industry-4-0/manufacturing-industry/
https://medium.com/@i4ms_eu/data-driven-smart-manufacturing-how-data-can-empower-decisions-on-the-shop-floor-
33ae477b5198
https://www.businessfinland.fi/en/whats-new/calls/2020/european-call-for-innovative-
smart-manufacturing-projects-within-the-smart-eureka-cluster/

7. Why?
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Karan Menon
Stand Out countries are highly digitally
advanced and exhibit high momentum.
Stall Out countries enjoy a high state of digital
advancement while exhibiting slowing
momentum.
Break Out countries are low-scoring in their
current states of digitalization but are evolving
rapidly.
Watch Out countries face significant
challenges with their low state of digitalization
and low momentum; in some cases, these
countries are moving backward in their pace of
digitalization.
https://hbr.org/2017/07/60-countries-digital-competitiveness-indexed

8. Why is industrial internet so good for business?
a sharp decline in the cost of sensors and, thanks to advances in cloud computing, a
rapid decrease in the cost of storing and processing data
Machines have become
Predictive, Reactive and Social
Source:
https://archive.org/details/MarcoAnnunziata_2013S
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9. Change in the way we sell
Porter, Michael E., and James E. Heppelmann. "How smart, connected products are transforming competition." Harvard business review 92.11 (2014): 64-88.
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10. Evolution to non-ownership business models
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Karan Menon
Traditional selling
based business
model
Rental /
Leasing
Pay-per-
Use
(PPU)
Pay-per-
Outcome
(PPO)
Pay-per-
Output

11. Characteristics of data-driven business models
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Karan Menon Kohtamäki, M., Parida, V., Oghazi, P., Gebauer, H., & Baines, T. (2019). Digital servitization
business models in ecosystems: A theory of the firm. Journal of Business Research, 104, 380-392.
• Increased customization of
products and services (based
on data and software)
• Increased optimization and
automatization of processes
(Digitalisation)
• Developed (dynamic) pricing
(from static mainly investment
pricing towards use and
value/outcome based pricing
(Pricing)

12. SMEs and non-ownership business models
Pros n Cons
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Karan Menon
Why SMEs?
• SMEs represent over 99% of the companies located in the EU1
• SMEs hire between 50 and 70% of the full time equivalent of persons employed1
• SMEs have a gross value added share of over 50% of the European economy1
What are SME manufacturing company issues?
• Lack of resources, expertise, competences
• High quality product manufacturers with restricted market access
• Competition from the big players
• Day-to-day survival issues
What can Non-ownership business models do to solve these issues?
• Risk distribution
• Steady, continuous and more predictable income flow
• Easier faster to sell products to the customer in this way instead of just investment manner
• New niche markets
• New opportunities for growth and strategic benefits – Sales growth, Market share expansion, New market creation2
• Internationalisation
Reference:
1. Müller, Julian Marius, Oana
Buliga, and Kai-Ingo Voigt.
"Fortune favors the prepared:
How SMEs approach business
model innovations in Industry
4.0." Technological
Forecasting and Social
Change 132 (2018): 2-17.
2. Gebauer, Heiko, Mirella
Haldimann, and Caroline
Jennings Saul. "Competing in
business-to-business sectors
through pay-per-use
services." Journal of Service
Management 28.5 (2017): 914-
935.

13. Tools to implement non-ownership business models: Morphological Box
• Companies understand the benefits of non-ownership
business models
• Yet, many struggle with the transition
• Hence, many initiatives lead to:
• unsuccessful pilot projects,
• non-sustainable business models,
• unhappy customers,
• unhappy employees, …
• Reasons for the struggle include:
• unclear objectives (where do we want to go),
• unclear baseline (where are we today),
• neglecting key elements,
• lack of awareness of possible options, …
Ownership
Operations
Transactions
Key Elements of Morphological box:
Value Exchange Components
This was our motivation to investigate how we can help
companies interested in non-ownership business models
but are struggling
Our approach:
Morphological Box as a framework to describe and define
non-ownership Business Models
- Work in progress -
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14. Tools to implement non-ownership business models: Morphological Box
- Work in progress -
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15. Morphological Box: Example using a real case
- Work in progress -
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16. Morphological box process
Assess Envision Define
Osterwalder & Pigneur, 2010
• Use MB to map current practices
• Understand Status Quo
• Identify inconsistencies
• etc.
• Define the envisioned BM
• Identify necessary changes from
current practices
• Identify missing capabilities
• etc.
• Once future vision is mapped, detail BM
using the BM Canvas
• Translate the key elements into a
unique BM reflecting the values,
capabilities, and resources of the
organization
• etc.
- Work in progress -
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17. Case (Caterpillar) – Data to maximize the machine efficinecy (Digital-
Add Ons, Freemium)
Reference - Schaefer, D., Walker, J., & Flynn, J. (2017). A data-driven business model framework for value
capture in Industry 4.0. Advances in Manufacturing Technology XXXI, 245-250.
• Caterpillar construction equipment division is one of the pioneering companies in the construction sector.
• In 2015, CAT announced its ambition to incorporate data-driven products and services into its corporate
strategy.
• Caterpillar’s group president for customer and deal support, Rob Charter, said “We can transform the
mountains of incoming data – from a single machine or engine, an entire job site, the supply chain, a shipping
location and much more – into valuable information for our customers and suppliers.”
• The change in the business models.
• Caterpillar will use data from embedded sensors to inform a new maintenance schedule revenue stream that uses data
analytics to maximize the lifespan and efficiency of deployed equipment.
• In order to achieve this, Caterpillar opened a Data Innovation Lab at the University of Illinois in 2016 to turn “customer and
market data into valuable information for the growth”
• This led to a variety of BM options for CAT
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18. Case (Caterpillar) – Data to maximize the machine efficinecy
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Reference - https://www.businessmodelsinc.com/business-model-caterpillar/

19. Key take aways
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• Technology enables better calculation power, real-time/near real-time data access
• Connectivity has gone up with 4G, LTE and 5G connections
• AI, Blockchain, Industrial Internet/Industry 4.0 makes manufacturing more transparent, accurate and fast
• Advantages of the technology should be translated in the business related value creation
• Digital Transformation should be connected to business model change and transformation
• Non-ownership business models and traditional selling business models should make new hybrid
models
• SMEs can access niche markets, create continuous earnings, internationalize and grow faster
• Morphological Box allows you to assess and configure the advanced business model that suits your firm
• Finally, nothing will work if the mindset does not change with the technological and business model
evolution

20. What are we doing on this topic?
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Karan Menon
Business Finland Projects
• SNOBI Project (https://projects.tuni.fi/snobi/)
• 5 Industrial companies (2 SMEs)
• Overall Budget 4.2M€
• The objective of the SNOBI project is to design and implement the systematic transformation process from traditional business models to advanced
PPX type business models in investment product manufacturing SME equipment companies.
• Future Spaces Project (https://www.futurespace.fi/)
• 11 Companies (Industrial companies, municipalities, real estate companies)
• Overall Budget 3.67M€
• The goal of this project is to research and develop novel business models (for example non-ownership business models) for the real estate
modernization market, combining construction and building engineering technology expertise with the improvement and management of indoor
conditions in the existing real estates.
• DIMECC Business Model Academy (https://www.dimecc.com/dimecc-services/bma/)
• 12 Industrial Companies
• DIMECC’s Business Model Academy (BMA) helps companies identify and deploy data-driven business models.
• BMA helps business leaders adopt systematic approach for creating and implementing profit-generating ideas that leverage existing products and
solutions, markets, customer relationships, and infrastructure.

21. Kiitos! Thank
you! धन्यवाद
Contact Information
Email– karan.menon@tuni.fi
Twitter - @menonkaran
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