1. Do we understand what is coming towards us ?
PLM – SOMETHING HAS TO CHANGE
Jos Voskuil
www.virtualdutchman.com
2. Continuous transformation & learning
2013 - Integrating PLM, CM and SE for lean,
innovative and agile operations
2014 - Shaping the PLM Platform of the Future
2015 - The Perfect Storm for PLM – The Product
Innovation Platform
2016 - Investing for the future while managing
product data legacy and obsolescence
4. Wherearewewith digital transformation ?
McKinsey: The case for digital reinvention
• Products and Services
• Marketing and Distribution channels
• Business Processes
• Supply Chains
• new entrants acting in Ecosystems.
Where to make your
digital investments ?
Digitization is putting pressure on
revenue and profit growth
Uneven returns on investment
5. Wherearewith digital transformation ?
McKinsey: The case for digital reinvention
47 %
60 %
52 %
48 %
43 %
Average level of digitization
Bold strategies win !
11. Digital Enterpriseassumptions
Apps / APIs / micro services
? ? ? ? ? ? ?
Here is where the money is made !
Reduced amount of resources/ Quality / Intelligence / Selling Insights
12. The Product Innovation Platform needs to bedata-driven
Data Quality and Master Data Management
The role of the Product Innovation platform
How to identify the correct
Master Data subject areas
& tooling for your MDM
initiative.
Christopher Bradley
(SlideShare) PLM
ISO 15926
PLCS
OSLC
Others ..
Where are the Data Quality initiatives ?
15. The Model Based Enterprisealong the lifecycle
A Model-based Enterprise moves the record of authority from
documents to digital models including MCAD, E-CAD, SysML and
UML managed in a data rich environment.
Model-Based is the foundation for automation (AI, Algorithms, Simulation)
Model-Based Systems Engineering ,Model Based Definition (PMI),
Digital Twin are all related.
FAKE NEWS
16. Moving toa Model-Based Enterprise isa journey
Image: J.B. Herron – Action Engineering – Re-use your CAD
17. Experienceswith some largeenterprises
Most choose for the evolutionary approach.
Big bang is too risky – not because of technology
Evolution fails, due to several reasons:
Top-down strategy becomes too often an IT-rationalization
Time to understand – too many pilots – no commitments
Continuous excitement and vision needed
Career politics – P&L vertical approach
Short term strategy due to investors demands
Jan Bosch -The End of Innovation (as we know it)
18. What’s next ? Evolutionaryapproaches
KPMG: beyond the hype separating ambition from reality in i4.0
McKinsey – our insights/toward an integrated technology operating model
“Companies will need to adapt their cultures in ways that
will appeal to both next-generation digital workers”
“Take bold steps towards integration”
“Be prepared to make big and bold decisions”
“The war for talent requires creativity and
not a risk-free pension strategy”
19. Experienceswith somesmall and medium enterprises
Many of them have no time for strategy
Optimized for performing in current market
No evolutionary thinking
Family-owned business can make a difference
Long-term strategy possible
Survival through attracting the right inspirators
Unpredictable dynamics – Do or Die.
20. What’s next forSmall and Medium Enterprises ?
Awareness beyond marketing
Management needs to own the vision
Education
Universities / Government initiatives
Task forces / Conferences
Coaching
best practices / business change
21. Conclusions
We make progress understanding the role of PLM
in a lifecycle Model-Based enterprise – concepts are
still in early phases.
The incompatibility of current PLM and digital PLM
requires an accelerated evolution supported by
MDM / Model-Based transitions
A bold vision and clear commitment from the top is needed.
Create a horizontal path in the enterprise connecting
the Why (business), How (change) and What (tools)