Pl mx 2018 hamburg plm transformation and digitization
1. What are the mandatory steps and why ?
PLMTRANSFORMATIONALONGSIDE DIGITIZATION
Jos Voskuil
www.virtualdutchman.com
Join the discussion on:
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2. 1999 Artificial Intelligence ?
TacIT – JosVoskuil @josvoskuil
2008
PLM Coach, Consultant, Translator
Assisting companies, implementers and
vendors in all facets of the PLM lifecycle
with a current focus on digitization.
PLM ?
10 Years!!
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 !
PLM !
PLM ?
PLM ?
PLM !
6. PLM – the forgottendomain ?
Document-driven approach
Products
Inside out: push to the market
Waterfall
11. The futureof software: Digital Platformsworking together
CIMdata Product Innovation Platform
The future is “federated”
12. Old and New PLM are notcompatible
Incompatible
ECR/ECO/NCR/ …. Algorithms / blockchain based
authorizations / AI
THEY WILL BOTH EXIST !
13. The future is based on DATA - it needs to bereliable
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
Or ? ..
Where are the Data Quality initiatives ?
PLM Vendors do
not talk about
MDM (yet)
Product MDM
Customer MDM
14. From Drawings to Items to Models – the importanceof 3D
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.
Connected 3D models are needed if we want to
benefit from augmented reality, virtual twins
without spending too much work on converting
collecting data – we want a digital thread.
15. Moving toa Model-Based Enterprise isa journey
Image: J.B. Herron – Action Engineering – Re-use your CAD
Most
companies
are here !
16. Digital Twin – taking benefits from IoTwe need digital PLM
Modern, digital PLM plays a role in digital twin scenarios
• Use real-time data to optimize your simulation models
• Use virtual models, simulations to prepare for the
physical world – flexible manufacturing processes
20. 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)
21. 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”
“The war for talent requires creativity
22. 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.
23. Conclusions
We need to get PLM out of the engineering box by talking
about the Why and less on the What. Talk value not features
24. Conclusions
We need to get PLM out of the engineering box by talking
about the Why and less on the What. Talk value not features
Current and Future PLM are incompatible.
Adjust your strategy – think along bimodal
Avoid endless Proof of Concepts. Act !
25. Conclusions
We need to get PLM out of the engineering box by talking
about the Why and less on the What. Talk value not features
Current and Future PLM are incompatible.
Adjust your strategy – think along bimodal
Avoid endless Proof of Concepts. Act !
Reduce the gap by investing in Data Quality (MDM),
Model-Based ways-of-working.
26. Conclusions
We need to get PLM out of the engineering box by talking
about the Why and less on the What. Talk value not features
Current and Future PLM are incompatible.
Adjust your strategy – think along bimodal
Avoid endless Proof of Concepts. Act !
Reduce the gap by investing in Data Quality (MDM),
Model-Based ways-of-working.
Focus on committed leadership in your company.
Change never happens bottom-up
27. Conclusions
We need to get PLM out of the engineering box by talking
about the Why and less on the What. Talk value not features
Current and Future PLM are incompatible.
Adjust your strategy – think along bimodal
Avoid endless Proof of Concepts. Act !
Reduce the gap by investing in data quality (MDM),
Model-Based ways-of-working.
Focus on committed leadership in your company.
Change never happens bottom-up
There is a war for talent !