The document discusses building IoT driven platforms and the evolution of IoT platforms. It provides examples of different types of IoT platforms including matchmaking platforms that optimize supply and demand, process automation platforms that connect shippers and carriers, and analytical intelligence platforms that provide real-time data processing and decision support. Successful IoT platforms create multi-dimensional and continuous value for producers and consumers through services and business models that range from transactional to based on outcomes and usage.

1. BUILDING IOT DRIVEN PLATFORMS
The NEXT LEVEL of INDUSTRIAL INTERNET

2. MAINTENANCE IS MAINSTREAM
Successful platform business yields higher results than maintenance
Source: goetzpartners client interviews B2B industries 2015/16
-10
0
10
20
30
40 IOT PLATFORMS
IOT MAINTENANCE
SOLUTIONS
t
PROFITABILITY COMPARISON (%)

3. (B2B) PLATFORM VALUE PRINCIPLES
Value
adding
services
Source: goetzpartners
Multi-dimensional, continuous value
creation for all participants
PRODUCER CONSUMER

4. IOT PLATFORM EVOLUTION
TYPE OF VALUE PROPOSITION
Decision (Semi-)Automation
Decision Support
Transaction Costs
Search Support
DOMINANT BUSINESS MODEL
Source: goetzpartners
Usage OutcomeTransaction
COG-
NITIVE
ANALYTICAL
INTELLIGENCE
PROCESS
AUTOMATION
MATCHMAKING

5. EXAMPLE 1: MATCHMAKING
Source: MakeTime, goetzpartners
MATCHING ALGORITHM &
MARKET PRICING
 Project requirements
 Capacity availability
 Equipment & expertise
 Material availability
 Geographical location
UTILIZATION
OPTIMIZATION
SUPPLY CHAIN
FLEXIBILTY
03/15 04/15 01/16 02/16
4,409,590/HRS
Available
All Machines EDM CNC Laser CNC Lathe CNC Mill
CNC Plasma
Cutter
CNC Router
CNC Swiss-
Type
CNC Water Jet CNC Punch

6. Source: Transporeon, goetzpartners
EXAMPLE 2: PROCESS AUTOMATION
Connects >1,000 shippers with
>55,000 smaller carriers creating
a new market
 Better utilization for carriers
 Lower freight rates for shippers
SHIPPER
LARGE CARRIERS SMALLER CARRIERS
EDI

7. EXAMPLE 3: ANALYTICAL INTELLIGENCE
Source: Siemens, goetzpartners
MINDSPHERE IOT CLOUD
 Open ecosystem for machine
building/manufacturing
industry
 High safety standards
ANALYTICAL INTELLIGENCE
 Real-time in-memory data
processing
 Rule-based decision support
CONNECTIVITY
 Assets from Siemens and
other OEMs
 >300k industry devices,
millions of sensors
MIND APPS
 Siemens analytics apps
 SDK for customers
& third party developers
MINDSPHERE
IOT CLOUD
INDUSTRIAL
USERS
DEVELOPERS
MindApps
Connected assets

8.  Ecosystem building
with 50+ IoT business
partners
 Acquisitive growth in
leading AI disciplines
& industry sectors
 x-vertical industry
expertise
Source: IBM Watson, goetzpartners
LEVERAGING PLATFORM
TECHNOLOY
ACROSS MULTIPLE
DIMENSIONS
Use Case | CT Scan Interpretation
EXAMPLE 4: COGNITIVE INTELLIGENCE
Payor
Doctor
Patient
BETTER & FASTER
TREATMENT
(SEMI-)AUTOMATED
DECISION SUPPORT
MEDICAL EXPENSE
OPTIMIZATION

9. SHOULD OUR FIRM INVEST IN PLATFORMS?
1|  Market inefficiencies and
intransparencies
 Unexploited business
opportunities
 # of addressable participants
(demand & supply side)
 # of inducible transactions
 Technological capabilities
 Ecosystem capabilities
 Business model & case
Yes No
Yes No
Yes No
IOT BUSINESS
ALTERNATIVE
IOT
PLATFORM
Source: goetzpartners
SOLVES IDENTIFIED
INDUSTRY PAIN POINT
2|SCALING
POSSIBILITIES EXIST
3|MONETIZATION
PATH IS TANGIBLE

10. KEY SUCCESS FACTORS
Source: goetzpartners
SCALE FIRST
MONETIZE LATER
NEW BUSINESS MODELS
 Flexible usage-based models
 Performance-based pricing
ECOSYSTEM BUILDING
 Ensure data access via own sensors/partnering
 3rd party engagement (external developers)
COLLABORATIVE APPROACH
 Joint, iterative development within a close
collaboration with customers
HYGIENE FACTORS
 Open, vendor-agnostic IoT platform concept
 Ensuring data security & privacy

11. THANK YOU!