Data-based business models: How to turn your data into a goldmine?

Stuttgart, 10.12.2019
Data-based business models:
How to turn your data into a goldmine?

diconium | Fast track to digital leadership 2
Total expected market size
for data monetization by 2023
DATA MONETIZATION POTENTIAL: As long as organizations do not know how to apply data
within their business models, data will not become the new gold
$ 370 bn1
~ GDP of South Africa2
But how to transfer the market potential into
business models?
Sources:
(1) By end user. Allied Market Research
(2) Nominal GDP in 2018, Trading Economics

diconium | Fast track to digital leadership
?
3
CONTENT: The diconium Data Platform Quadrant guides you with two maturity dimensions
for developing and monetizing your data-based business models
The Data Market
Digital
Commerce
Maturity Level
Data Platform
Quadrant
Data Product
Maturity Level
Benchmarks
Benchmarks
Five Goldbar
Rules
Industry
Examples
Make or Buy

DICONIUM DATA PLATFORM QUADRANT: Four different business models can be
distinguished by using the two maturity dimensions along the axes
Identifying and initiating first
data exports within MVP.
Ensuring professional data sales within
a data marketplace environment.
Enhancing data product maturity level
and focusing on data transfer acceleration.
Offering a fully integrated, scalable data platform
with openness to 3rd parties.
DATA PLATFORM
DATA START-UP DATA SHOP
DATA EXPORTER
DATAPRODUCTMATURITYLEVEL
2
1
3
DIGITAL COMMERCE MATURITY LEVEL

DICONIUM DATA PLATFORM QUADRANT: Two ways shape the path as data start-up, the
combination in a platform approach leads to the most advanced form
Simple data with
basic e-commerce processes
Simple data with
advanced e-commerce processes
Sophisticated data with
basic e-commerce processes
Sophisticated data with
advanced e-commerce processes
DATA PLATFORM
DATA START-UP DATA SHOP
DATA EXPORTER
DATAPRODUCTMATURITYLEVEL
2
1
3
DIGITAL COMMERCE MATURITY LEVEL

Your mining equipment:
Lets talk about Data Product Maturity

DATA PRODUCT MATURITY LEVEL: As data start-up, basic raw data points, often
beginning with anonymous historical data sets, define the data product portfolio
Data Privacy
Data
Recency
Data
Character
Anonymized Personalized
Data insights
Raw data
Real-time
Historical
Intermediate Advanced
Data product maturity level
Starter
Starter data product maturity
1 2 3
 Raw data of a sensor e.g.
temperature information, energy
consumption or speed
 Capturing and exporting data with
defined time stamp
 Basic monetization potential mainly
defined by added value for the use
of data; price generation only by
data itself
 Manual data error handling

DATA PRODUCT MATURITY LEVEL: On an intermediate level, the portfolio extends as data
product value is added through a more processed data character
Data Privacy
Data
Recency
Data
Character
Data insights
Raw data
Real-time
Historical
1 2
Intermediate data product maturity
 From raw data to more concrete
data insights, e.g. prediction model
for temperature development
including recommendation
 Added value can be reached
through e.g. own data processing
and product on demand services
 Increased monetization potential for
data set e.g. by adding analytical
services for concrete business
value
 Semi-automated process of data
error handling
3
Starter

DATA PRODUCT MATURITY LEVEL: An advanced data product maturity is reached through
automated data enhancing processes for delivering straight data insights
Data Privacy
Data
Recency
Data
Character
Data insights
Raw data
Real-time
Historical
Advanced data product maturity
 Streaming of data with alert
function, e.g. telling a customer that
temperature in defined GPS grid is
below a configured level (e.g. 6°C)
 Including 3rd party data, e.g.
validated by of World
Meteorological Organization
(WMO) and anticipation of
temperature forecast model
 Fully optimized data monetization
potential due to automated insights
derivation
 Automated process of data error
handling
1 2 3
Starter

Existing goldmines:
What are exemplary benchmarks?

BENCHMARKS: While Here offers a location-centric data platform, Google focuses on API
access for cloud services and BASF provides direct data insights (weather)
1 2 3
FORECAST PLATFORM
Aggregated data platform for
direct business insights
OPEN LOCATIONPLATFROM
Collaboration-oriented Map
service platform
CLOUD PLATFORM
Deployment- and operating oriented
platform
Picture Sources:
(1) https://developer.here.com/products/open-location-platform
(2) https://cloud.google.com/blog/products/gcp/enterprise-identity-made-easy-in-gcp-with-cloud-identity
(3) https://agriculture.basf.com/us/en/Crop-Protection/Weather.html

Goldmine operations:
Digital Commerce Maturity Level

DATA START-UP: Payment and fulfillment services are MVP essentials within the e-
commerce value chain for selling data to customers
PROCUREMENT
CONTENT
CREATION
ONLINE
MARKETING
ONLINE
DISTRIBUTION
FINANCE/
PAYMENT
FULFILLMENT
CUSTOMER
SERVICE
1 2 3
Finance/Payment
 Payment and subscription contracting are essentials.
 Evaluate the value of the data.
 Set up subscription contracts including the frequency of data exchange and volume of data.
 Give customers access to the contracts and invoices.
 Selling data is all about metering of data. Give customers access to the metering.
Fulfillment
 Delivering data in an automated way is essential and needs to be defined. Customer Success
Manager are supporting the customer in handling the data.
 Measurement of data flows are necessary right at the beginning and is needed for invoicing the
services.

DATA SHOP: Depending on the individual e-commerce maturity level all parts of the e-
commerce value chain help to increase efficiency and revenues from data
PROCUREMENT
CONTENT
CREATION
ONLINE
MARKETING
ONLINE
DISTRIBUTION
FINANCE/
PAYMENT
FULFILLMENT
CUSTOMER
SERVICE
 Data procurement
includes the
decision of the
legal setting.
Should a data
company be an
intermediate
company to sell
data to
customers?
 Automize data
procurement
 Establish
processes to
incorporate data
errors of data
suppliers
 Provision of meta
data, technical
und editorial
content
 Different usage
scenarios have to
be enabled by
quick start guide,
guidelines and
examples
 Definition of
relevant
marketing
channels
 Utilize content for
digital marketing
campaigns
 Promote new
data products by
addressing new
target groups
 Evaluate data
value
 Set up smart
contracts
including
frequency of data
exchange and
volume
 Give customers
access to
contracts and
invoices
 Give customers
access to the
metering
 Convenient (self-
service)
purchasing
process (e.g.
simple
onboarding,
several payment
possibilities etc.)
 Transparent
pricing with price
simulation
 Upfront testing of
data products
(e.g. trial period)
 Digital process for
customer specific
requirements
 Delivering data in
an automated way
is essential and
needs to be
defined
 Customer
Success Manager
are supporting the
customer in
handling the data
 Measurement of
data flows is
necessary and
needed for
invoicing
 Definition of
customer service
channels and
ticket handling
 Definition of sales
service support
and customer
service is needed
 Customer
guidance through
out the entire
Customer
Journey
 Proactive
communication of
data errors und
correction
procedures
1 2 3

Again, what are exemplary benchmarks?

BENCHMARKS along the Value Chain: Here offers a lot of content for their customers and
developers. Google creates price transparency with a calculator
PROCUREMENT
CONTENT
CREATION
ONLINE
MARKETING
ONLINE
DISTRIBUTION
FINANCE/
PAYMENT
FULFILLMENT
CUSTOMER
SERVICE
ContentCreationOnlineDistribution
• Here produces a variety of content to assist customers through Quick Start, Guidance and Examples
• Here also produces content to inspire customers how to use their products within their blog
• https://developer.here.com/documentation/park-and-ride/dev_guide/topics/quick-start-parknride.html
1 2 3
• Google like 200 Dollars for free to test the provided data
• Pricing Calculator to estimate expenses
• https://mapsplatformtransition.withgoogle.com/calculator
Picture Sources:
(1) https://developer.here.com/documentation/park-and-ride/dev_guide/topics/quick-start-parknride.html
(2) https://mapsplatformtransition.withgoogle.com/calculator

BENCHMARKS along the Value Chain: DAWEX provides an easy onboarding process and
TWITTER shows its enhanced service availability
PROCUREMENT
CONTENT
CREATION
ONLINE
MARKETING
ONLINE
DISTRIBUTION
FINANCE/
PAYMENT
FULFILLMENT
CUSTOMER
SERVICE
OnlineDistributionCustomerService
• DAWEX, a global data market place, provides an easy onboarding process
with email, phone and LinkedIn verification
• After the verification of the a back office team, data can be purchased or
can be offered in an easy way
1 2 3
• Twitter shows the
real time status of
data availability
• Twitter give transparency about the
last incidents in a log
• https://api.twitterstat.us/
Picture Sources:
(1) https://www.dawex.com/de/
(2) https://api.twitterstat.us/

The real nugget, the data platform!

DATA PLATFORM: Data insights, fully mature e-commerce processes and openness
transform the data shop or data exporter into a real data platform
1 2 3
Provide real data insights (e.g. enabled by 3rd party data)
instead of pure raw data
Leverage all capabilities of the e-commerce value chain to
provide a convenient customer experience
Transform the data shop / data exporter to a real data platform by …
… investing in convenient and automized processes to be more customer centric and push gravity
… enabling a developer community to enable collaboration and increase network effects
… onboarding of 3rd party data provider on your platform to offer more relevant content for your customers
… providing additional services to your customers that increase a log-in effect by convenience
 Receive more insights about platform business in the whitepaper “A world of platform business”.

What is our experience?

FIVE GOLDBAR RULES for the establishment of a data market place concerning technical,
organizational and process-oriented recommendations
Build a single
solution and
start with an
MVP approach
Create, scale,
and customize
the platform
components
Embed an agile
model into your
organization
Ensure legally
compliant data
transfer
processes
Continuously
improve data
enrichment for
Platform USPs

Conquering new claims:
Which industry is next?

THINK AHEAD OF YOUR INDUSTRY! Assess data already being collected and identify the
potential re-use for other companies to improve their services
Trucks, containerships, trains etc. are
collecting data, so forwarder and other
companies can improve their service.
TRANSPORTATION
Sensors placed on construction sites,
equipment, materials or even
wearables of workers exist to improve
the construction work.
CONSTRUCTION
Airplanes are measuring flight data to
optimize flight conditions and the
travel experience.
AEROSPACE
& AIRLINES
Data in those and other industries can be monetized to improve services of other companies.
Evaluate which data could be gathered, for what it can be analyzed, in what way it can be packaged
and by what channel and measurements it can be sold.
DATAINDUSTRYGOLDMINE

Final question to consider:
Make or buy?

Exploring the right data to be monetized needs to become a
core capability of the company.
Companies need to invest into that exploration, either by
high value hiring or by cooperation.
25
AS ALWAYS – MAKE OR BUY? Generating data insights is the core competency for data-
based business models, e-commerce building blocks can be outsourced
Make it your future core competency!
E-commerce capabilities can be bought from different
companies up to platforms providing everything in a
convenient way, which are coming at a certain cost.
Buy for quick start, insource when sufficient
economies of scale can be realized inhouse
!
Picture Sources:
(1) https://www.dawex.com/de/
(2) https://aws.amazon.com/de/data-exchange/

Let’s find it out together!

INNOVATION &
STRATEGY
DATA & AI
TRANSFORMATION
TECHNOLOGY
SOLUTIONS
CUSTOMER
EXPERIENCE
eCommerce solutions
Data platforms
Digital transformation
Change management
Company building
Legal setup for the data unit
Cloud architecture
Data platform architecture
Commerce architecture
API Design
COMMERCE
SOLUTIONS
Definition of the Customer journey
User experience concept
User interface design
Content strategy & management
Ideation of data products
Digital business models
Digital strategy
IT strategy
eCommerce
Platform strategy
Data strategy
OUR DATA COMPETENCIES
We help using your data monetization potential with our 360° approach
DIGITAL
BUSINESS
EXCELLENCE
Concept for (advanced) data products
Data Analytics
Data science & AI

YOUR CONTACT
Andreas Hell
management consultant
Nina Böckenholt
management consultant
Andreas.Hell@diconium.com
Phone: +49 711 2992-3587
Mobile: +49 162 2102463
Nina.Boeckenholt@diconium.com
Phone: +49 711 2992-3347
Mobile: +49 173 2947729
29
director
Carsten Klenner
Carsten.Klenner@diconium.com
Phone: +49 711 2992-3314
Mobile: +49 151 14202500

Data-based business models: How to turn your data into a goldmine?

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