4. J O S E P H I N E S C H O LT E S | P R O D U C T M A N A G E R
5. • Implementing & customizing Microsoft products
for our customers (large corporations)
• Work across countries & industries on a project
basis
• Background in experience design & design
strategy
12. • Digital Twins involve a lot of data and insights. And so, it’s
important to consider who needs to see what
• Standardizing data collection and connection
• Scalability requires breaking down silos and creating ecosystems of
digital twins
13. Data Literacy & Adoption
“Watermelon KPIs: they look green on the outside
but are red on the inside.”
“Here comes the voodoo data”
17. Customer says: “We want insights.”
VALUE
COMPLEXITY
Descriptive
What happened?
Diagnostic
Why did it happen?
Predictive
What is likely to
happen in the
future?
Prescriptive
What’s the best
course of action?
18. Customer says: “We want predictive .”
DATA
POINT
DATA
POINT
+ = DATA INSIGHT
19. Customer says: “We want predictive .”
Machine
Name
Time
between
errors
+ =
“I want to see what
machines will require
maintenance in the
future.”
20.
21.
22.
23. Laying out all options as a conversation starter
Data Scientists write down… Business / UX write down…
24. Laying out all options as a conversation starter
Data Scientists write down… Business / UX write down…
28. Going from Keyword to Multi Term Search.
Transforming search experiences
29. Going from Keyword to Multi Term Search.
Transforming search experiences
30. Service Blueprint
Defining how generative AI is
integrated in specific channels
and touchpoints in the customer
journey.
E.g. generic search, help &
support, chatbot.
41. • When envisioning emerging tech, it is important to bridge the gap
between business & tech
• Clearly define what we are talking about
• Lay out all the options – make it visual and tangible to ensure
collaboration
Translating complex concepts into something that’s understandable and tangible/visual
Digital Twin is not a product, it’s a process
Data collection poses a significant challenge and thus standardization in connecting data to digital twins is required
Breaking down silos and creating ecosystems of digital twins to get more value