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Dynamics Day 2015
Systems of Intelligence in Action
Experimentation
!=
Learning From
Mistakes
1
MALLEABLE: It must be cost effective to change the
way that the system or process behaves. Ideally for
just a subset of ...
MALLEABLE
OBSERVABLEENGAGED
“arguments about whether or not a
feature idea is worth doing or not
generally get resolved by just spending a
week implem...
There are over 500 different K-Cups
There Are Cartridge Loaded Software Systems
Microsoft Azure Demand Center
Internal Systems & Product/Platforms
Dynamics CRM
Marketo
Web Email Call Center
Data
Warehou...
MALLEABLE
OBSERVABLEENGAGED
Storage is Cheap…
…Data Is Not
Smart Appliances (Think Printers + Ink)
Existing ‘Dumb’ Product
SensorTag
IoT Suite
Smart Screen Mobile Apps(s)
Raw Data S...
MALLEABLE
OBSERVABLEENGAGED
“…Our tool works best when you’ve got at
least 1 million or so app installs to work
with…”
Towards Systems
of Intelligence
Flipping The Model
Inputs OutputsIT System
Expertise
InterpretationExperimentation
Flipping The Model
Inputs OutputsIT System
ExplanationExperimentation
Automation
Models
Machine Learning
Example:
Building Systems
Provider (~HVAC)
Much of the Tooling
is Free
Is Becoming More
Widely Available
Is Becoming Easier to Use
And Is Entering The Public Consciousness
And can be crowd-sourced
In Boots & All
Use Cases We Are Seeing
Big Data Use Cases, BARC Research 2015
STORE
OPTIMIZATION
TRACKING,
TARGETING
SEGMENT OF 1
SMART
PRODUCTS
SMART
ASSETS
PRODUCT
IMPROVEMENT
CUSTOMER
ACQUISITION &...
• Embrace Experimentation
• Malleable, Agile, Cartridges
• Observable; Capture More Data
• Engaged; Ship Early & Learn
• S...
Dynamics Day 2015: Systems of Intelligence in Action
Dynamics Day 2015: Systems of Intelligence in Action
Dynamics Day 2015: Systems of Intelligence in Action
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Dynamics Day 2015: Systems of Intelligence in Action

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Using the cloud, the Internet of Things and machine learning to drive better outcomes for businesses and their customers.

Dynamics Day is Australasia's leading event for users of Microsoft Dynamics. Dynamics Day 2015 was focused on giving Microsoft Dynamics users the information they need to get the most out of their investments in the Dynamics range, or to help organisations who are considering any of these solutions insights into what's possible and what's on the roadmap in the future.

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Dynamics Day 2015: Systems of Intelligence in Action

  1. 1. Dynamics Day 2015 Systems of Intelligence in Action
  2. 2. Experimentation != Learning From Mistakes
  3. 3. 1 MALLEABLE: It must be cost effective to change the way that the system or process behaves. Ideally for just a subset of usage or users. WHAT WE NEED 2 3 OBSERVABLE: The system or process must be sufficiently well instrumented such that we have the information available to test the hypothesis. ENGAGED: The system or process must be being used at sufficient scale and in a sufficiently ‘real’ environment for any results to be significant. An experiment is a procedure carried out to verify, refute, or establish the validity of a hypothesis… Experiments vary greatly in goal and scale, but always rely on repeatable procedure and logical analysis of the results. SYSTEMS OF EXPERIMENTATION MALLEABLE OBSERVABLEENGAGED Experiments
  4. 4. MALLEABLE OBSERVABLEENGAGED
  5. 5. “arguments about whether or not a feature idea is worth doing or not generally get resolved by just spending a week implementing it and then testing it on a sample of users, e.g., 1% of Nevada users.”
  6. 6. There are over 500 different K-Cups
  7. 7. There Are Cartridge Loaded Software Systems
  8. 8. Microsoft Azure Demand Center Internal Systems & Product/Platforms Dynamics CRM Marketo Web Email Call Center Data Warehouse PowerBI Systems Of Record Systems Of Experimentation Systems Of Engagement
  9. 9. MALLEABLE OBSERVABLEENGAGED
  10. 10. Storage is Cheap… …Data Is Not
  11. 11. Smart Appliances (Think Printers + Ink) Existing ‘Dumb’ Product SensorTag IoT Suite Smart Screen Mobile Apps(s) Raw Data Store ??? Personalization Platform PowerBI Systems Of Experimentation Systems Of Engagement
  12. 12. MALLEABLE OBSERVABLEENGAGED
  13. 13. “…Our tool works best when you’ve got at least 1 million or so app installs to work with…”
  14. 14. Towards Systems of Intelligence
  15. 15. Flipping The Model Inputs OutputsIT System Expertise InterpretationExperimentation
  16. 16. Flipping The Model Inputs OutputsIT System ExplanationExperimentation Automation Models Machine Learning
  17. 17. Example: Building Systems Provider (~HVAC)
  18. 18. Much of the Tooling is Free
  19. 19. Is Becoming More Widely Available
  20. 20. Is Becoming Easier to Use
  21. 21. And Is Entering The Public Consciousness
  22. 22. And can be crowd-sourced
  23. 23. In Boots & All Use Cases We Are Seeing
  24. 24. Big Data Use Cases, BARC Research 2015
  25. 25. STORE OPTIMIZATION TRACKING, TARGETING SEGMENT OF 1 SMART PRODUCTS SMART ASSETS PRODUCT IMPROVEMENT CUSTOMER ACQUISITION & RETENTION USER ANALYTICS & OPTIMIZATiON SERVICE/B2B RETAIL SUPPLY CHAIN FRAUD & COMPLIANCE
  26. 26. • Embrace Experimentation • Malleable, Agile, Cartridges • Observable; Capture More Data • Engaged; Ship Early & Learn • Systems of Intelligence • Doing Data Science <- Easier • Knowing What We Can Do <- Hard • Analytics Inside Your Organization • Survey for Opportunities • Most CRM Systems • Customer Facing Apps/Sites • IoT

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