Presentation slides at Sitra's event 19 September 2019 Jaana Sinipuro, Sitra Jyrki Suokas, Sitra Timo Seppälä, Research Institute of the Finnish Economy

1. The New Data
Economy
Rainmakers: How’s
Your Business?
19 September 2019
#IHAN
#fairdataeconomy
#NDERainmakers

2. The New Data Economy Rainmakers:
Trust as Competitive Edge
19.09.2019 Jaana Sinipuro @jsinipuro

3. SITRA’S CONTRIBUTION TO FINLAND’S EU PRESIDENCY
Transformation to a
carbon neutral
circular Europe
Europe as a
forerunner in
a fair data
economy
Economy of well-
being with impact
investing
- Opportunity to promote sustainable growth with a cross-cutting approach
- Brings EU countries and different political groups together – themes have broad approval
- Supports developing far-reaching effectiveness for European actors and opens global opportunities
What’s in it for the EU?

4. IHAN® Framework as an
enabler for Paradigm Shift
Our project aims to build the
framework for a fair and functioning
post-GDPR data economy.
The main objectives are to test and
create methods for data sharing and to
set up European-level rules and
guidelines for the human-driven use of
data.
INDIVIDUAL | PERMIT | DATA
Making it happen – together.
IHAN® FAIR DATA ECONOMY RAINMAKERS
IHAN® Project facilitating the
move towards Fair Data
Economy
Creating Capabilities for Consent-based Data
Sharing Ecosystems.
COMMON RULEBOOK | GUIDELINES
| ENABLING ARCHITECTURE
| “UUDISTAMO”
M A I N TA I N I N G T R U S T – E U R O P E ’ S B I G G E S T O P P O R T U N I T Y
FACT-BASED RECOMMENDATIONS
FOR CITIZENS & POLICY MAKERS

5. IHAN® as a project
- We define not just the principles and guidelines but also the
necessary components for the fair data economy.
- We pilot new concepts based on personal data in collaboration
with pioneering businesses across corporate, industrial and
national borders.
- We develop an easy way for individuals to identify reliable
services that use their data in a fair way.

6. Over one third of businesses
felt that GDPR has had a
positive effect in their
ability to work in the data
economy.
37%
Oui, tres bon! France 49%

7. Facilitating mindset change through practice
Create
awareness at
companies
interested in
finding new
ways to
compete
Introduce
fair data and
open
ecosystems
as ways to
sustainably
create new
value
Improve
organisations’
understanding
and readiness
for IHAN®
IHAN® for DEVELOPERS
Reference Architecture, IHAN Sandbox,
Open Source Components
IHAN® for BUSINESSES
Concept “UUDISTAMO”, Guidelines and
Frameworks, Test Ground for New Digital
Services
IHAN® for CITIZENS
Digital profile tests and recommendations
Fair Data Label?
PROJECT DELIVERABLES (EXIT)
GOVERNANCEMODEL&
STRATEGIESFOREXECUTION
IHAN® for POLICY MAKERS
Facts for policies
Roadmap
COLLABORATION WITH
INTERNATIONAL STAKEHOLDERS
SOCIETAL
AWARENESS
IHAN® PROJECT 2018–2021
To ensure IHAN®
framework support and
funding in EU funding
programmes
Mindset change
throught facts and
surveys
Highlight future
potential
CONTINUOUS STAKEHOLDER DIALOGUES
INTERNATIONAL ADVISORY BOARDS

8. Corpotate Citizenship -
principles
1. Accountability
2. Transparency
3. Ethical behaviour
4. Respect for stakeholder interests
5. Respect for the rule of law
6. Respect for international norms of
behavior
7. Respect for human rights
8. Sustainable Data Governance?
Source: ISO 26000:2010 Social Responsibility
The 7 Principles
Ask yourself: would you
be comfortable if your
actions were to become
public knowledge?
ISO 26000:2010 Clause 2.7
about Ethical Behaviour

9. European companies are
starting to see the light at
the end of the tunnel
Jyrki Suokas
Data economy - Company survey 2019

10. Main findings
1. SMEs have difficulty building competitive edge in data economy.
2. GDPR high achievers understand the value of their data repositories and
are ready to create new data-based products and services.
3. French businesses show highest interest towards the Fair Data label.
4. Those with a positive attitude towards data economy are realistic about
the threats and opportunities of the future.
5. One needs to be an ecosystem player to succeed in data economy – Dutch
companies have the lead

11. Basic survey data
- The purpose of the study was to gain insight on companies’ awareness, attitudes, and
commitment to business potential enabled by fair data economy.
- Data economy is commonly understood as part of overall economy where
different operators work in the same environment in order to ensure
availability and usability of data and make use of data by refining it as a
basis in the creation of new services. In order to succeed in this, it is
imperative that operators in the data ecosystems share data with other
operators in the ecosystem.
- The data collection method used was a business decision-maker panel. Data collection was
carried out in April and May of 2019.
- The target population consisted of large enterprises and SMEs (excluding entrepreneurs) in
the Netherlands, Germany, France, and Finland. The study is based on 1667 responses.
- The study was carried out as a part of Sitra’s fair data economy IHAN project.

12. Most businesses see
possibilities in the data
economy now or in the
future.
Nojaa... Finland 42%
59%
Sitra’s company survey 2019 in Finland, France, Germany and the
Netherlands.

13. French, Dutch and German companies take very
optimistic view of the possibilities presented by data
economy. Finns are more pessimistic
Only 42% of the Finnish companies identify opportunities in data economy in the current
situation or in the future. French companies held the most positive views of all.
14% 18% 14% 12% 13%
27%
40%
26%
26% 18%
26%
19%
21% 28%
33%
33%
23%
39% 35% 36%
Germany FranceFinland
yes, it will in
the future
Netherlands
yes, it
already has
possibly
no
All
42%
69%
59%
Source: Sitra Business Survey 05/2019. Question: “Attitude towards data economy: Could data exchange produce competitive edge for your
company?” n = 1654
- The number of “No” answers
was nearly the same in each
country.
- 40% of Finnish companies
answered “possibly”, which
can be seen as a opportunity
to learn

14. Still less than half of SMEs are data economy optimists:
they see data economy as a competitive edge now or in
the future
SMEs’ take a slightly more pessimistic view on the possible competitive edges given by data economy
compared to those large companies who have already seen the light.
14% 10%
19%
27%
22%
32%
26%
28%
23%
33%
40%
26%
SMEsAll Corporations
yes, it
already has
no
possibly
yes, it will in
the future
59%
68%
49%
Source: Sitra Business Survey 05/2019. Question: “Attitude towards data economy: Could data econexchange produce competitive edge for
your company?” n = 1654
- Again the fact that 32% of
SMEs take a sceptical view is
a great opportunity for
learning and understanding
- One fifth of SMEs responded
“No”.

15. When assessing the business potential in the company’s
own industry and organisation, Finland comes last
Only 41% of Finnish companies see large or fairly large business potential in data economy for
their own organization. French companies held the most positive views (58%).
Source: Sitra Business Survey 05/2019. Question: “Attitude towards data economy: Please evaluate how much business potential you see
in data exchange in your business field/in your organisation?” n = 1635
- German and Dutch
companies form a middle
group when compared to
French in front and Finnish at
back
11%
13%
14%
16%
34%
33%
27%
26%
14%
12%
Own
Industry
Own
organisation
41%
38%
Finland Germany
Netherlands France
9%
9%
11% 33%
33%
31%
33%
16%
14%11%
Own
Industry
Own
organisation
47%
47%
9%
9%
36%
37%
37%
35%
13%
13%
6%
Own
Industry
6%
Own
organisation
49%
48%
7%
7%
29%
29%
41%
40%
16%
17%
6%Own
Industry
7%
Own
organisation
58%
57%
Fairly small
Small
Fairly large
Large
Neither large or small

16. When analysing the business potential according to the
main customer base (B2B/B2C), a noticeable difference is
found in the Finnish B2C sector
Only 38% of Finnish B2C companies find the business potential from data economy large or
fairly large compare to other countries in the study (55%).
Source: Sitra Business Survey 05/2019. Question: “Attitude towards data economy: Please evaluate how much business potential you see in
data exchange for your business field/organisation?” n = 1349
- The discrepancy between the
expectations of Finnish B2C
companies for own industry
and own organisation would
suggest lack of knowledge of
the current situation
- The difference between
Finland and the reference
countries both within B2C
and B2B sectors is substantial
11%
14%
14%
15%
29%
33%
30%
26%
16%
11%
Own
Industry
Own
organisation
38%
46%
Finland B2C Finland B2B
Other countries B2C Other countries B2B
7%
9%
14%
15%
37%
35%
29%
29%
13%
12%
Own
Industry
Own
organisation
41%
42%
8%
8%
28%
31%
44%
40%
14%
15%
6%
Own
Industry
6%
Own
organisation
58%
55%
33%
32%
36%
37%
16%
16%
5%
10%
6%
Own
Industry
10%Own
organisation
52%
53%
Small
Fairly large
Large
Fairly small
Neither large or small

17. The impact of platform giants on data economy is immense –
TOP3 challenges in each of the countries was to do with the
rules they are playing by and their market dominating size
When listing their challenges, the lack of know-how in Finland is more significant than in the
reference countries. Germany is the only country where GDPR is seen as a major challenge.
Source: Sitra Business Survey 05/2019. Which of the following do you see as the biggest challenges regarding the creation of new European
services that utilise data? (Choose max. 2 options”) n = 1635 (% of respondents)
- “The Americans and the
Chinese (Google, Facebook,
AirBnB, Alibaba) operate with
their own set of rules”, was
the most significant or the
second most significant
challenge for each country.
- And other TOP 3 challenge for
all four countries was also to
do with the platform economy
giant: “the existing players are
so large that competing with
them is futile”.
Finland Netherlands
Germany France
19%
Platform giants operate
on their own set of rules
Customers are not
requesting new services
Not enough know-how
The existing competitors
are already too large
32%
20%
22%
30%
34%
Not enough know-how
GDPR and other regulations
Platform giants operate
with their own set of rules
The existing competitors
are already too large 18%
16%
The existing competitors
are already too large
18%
25%Platform giants operate
on their own set of rules
20%
GDPR and other regulations
Not enough know-how
19%
Platform giants operate
on their own set of rules
The existing competitors
are already too large
GDPR and other regulations
Not enough know-how 19%
21%
34%
23%

18. Over one third of businesses
felt that GDPR has had a
positive effect in their
ability to work in the data
economy.
37%
Oui, tres bon! France 49%
Sitra’s company survey 2019 in Finland, France, Germany and the
Netherlands.

19. When comparing negative attitudes towards
GDPR the difference between French and Dutch
companies compared to Finnish ones is striking
The organisations who have completed their GDPR compliance project familiar with their data
repositories. 40% of Finnish companies – GDPR low achievers – do not see the regulation as an
opportunity.
13%
21%
14%
8% 10%
13%
19%
14%
11% 7%
37%
34%
38%
43%
34%
25%
18%
20% 29%
35%
12% 8%
14% 10% 14%
FinlandAll Germany FranceNetherlands
26%
49%
37%
40%
Source: Sitra Business Survey 05/2019. Claim: “Please evaluate the accuracy of the following statements that measure the maturity level of data
economy in your company on a scale from 1–5: The GDPR had a positive effect on our company’s chances of creating data economy” n = 1609
- The lower proportion (26%)
of GDPR high achievers
(responding “completely or
partly agree” to the question
about GDPR) in Finland
compared to the other
countries is also worth
noticing. The percentage of
GDPR high achievers in
France is 49%.
Totally accurate
Accurate
Totally
inaccurate
Inaccurate
Neutral

20. Effect of GDPR Country Competitive advantage Business potential
The GDPR high achievers have understood that a thorough
knowledge of their own data assets presents an opportunity
for new business – 75% are data economy optimists.
- GDPR high
achievers also
see much higher
business
potential for
their own
organization
than low
achievers
The GDPR high achievers (37% of companies) identify a significantly higher competitive edge and
business potential than the GDPR low achievers.
13%
13%
37%
25%
12%Very positive
Neutral
Positive
Negative
Very negative
37%
26%
18% 23% 27% 32%
France
Netherlands
Germany
Finland
40% 26% 19% 16%
France
Netherlands
Germany
Finland
19% 31% 44%
no
6%
yes, it
already haspossibly
yes, it will in
the future
75%
30% 33% 14% 23%
yes, it
already has
yes, it will in
the future
no
possibly
37%
3,81
2,73
Source: Sitra Business Survey 05/2019. Claim: The GDPR had a positive effect on our company’s chances of creating data economy.” n = 1654
Questions: “Attitude towards data economy: Could data economy produce competitive edge for your company?” and “Please evaluate on a scale
from 1 to 5 how much business potential you see in data exchange for your own company.”

21. Almost half of companies
thought that a Fair Data
label would be beneficial.
45% 66 % of consumers thought a label
would be important for services that
use data fairly.
Sitra’s company survey 2019 in Finland, France, Germany and the
Netherlands.

22. 12% 16% 14%
8% 11%
8%
13%
8%
7%
7%
34%
35%
34%
37% 29%
34%
26%
32% 39%
41%
11% 10% 12% 10% 12%
All Germany NetherlandsFinland France
36%
53%
45%
French companies show the highest confidence
in the Fair Data label.
The Finnish respondents stand out from others with less positive views: there was the lowest
proportion of those finding the label to be of high benefit or very high benefit (36%).
Source: Sitra Business Survey 05/2019. Question: “Consumer goods use the fair trade label for products that comply with the Fair Trade
requirements. Do you think a similar fair data label would benefit your company?”
Scale: 1 = No benefit at all 5 = Very high benefit
Very high benefit
High benefit
Some benefit
No benefit
No benefit at all
- 53% French respondents
as Finns found the label
beneficial.

23. Benefits of the FAIR DATA
label?
Country Importance of ethical rules? Is sharing data a good thing?
All of the respondents acknowledge the importance of
ethical rules for data collection and utilisation
- Finnish
companies were
over-
represented
among those
with a negative
attitude towards
the Fair Data
label with 36%.
Opinions about data sharing in general were clearly divided in line with the respondents’ attitude towards the
Fair Data label. Those with a positive attitude toward Fair Data were much more willing to share data with
other operators (3,84 vs. 2,88).
12%
8%
34%
34%
11%Very high
benefit
High benefit
Some benefit
No benefit
No benefit
at all
45%
21%
22% 22% 27% 29%
France
Netherlands
Germany
Finland
36% 25% 16% 22%
France
Netherlands
Germany
Finland
3,84
2,88
4,12
3,92
3,66
2,55
3,99
3,67
Source: Sitra Business Survey 05/2019. Question: “Consumer goods use the fair trade label for products that comply with the Fair Trade
requirements. Do you think a similar fair data label would benefit your company?”, “The view on and commitment to the statement ‘using and
collecting data must have ethical rules’”, and “the view on and commitment to the statement ‘sharing data with other players is a good thing’”.
View
Commitment

24. Data economy pessimists
do not even understand to be
worried about potentially lost
revenues
30%
Sitra’s company survey 2019 in Finland, France, Germany and the
Netherlands.

25. We used 2025 future scenarios to investigate the views
of the respondents on two alternative future trends
Current
situation
2019
2025 Future scenario 1
• digitisation and data economy undergo strong development led by large
global corporations
• there will be new platforms, but – just like today – operations focus on one
platform per business field and there is no room for other options
• consumers will not have genuine choice over or influence on how their
collected data is used
2025 Future scenario 2
• in collaboration with companies, the EU will invest in creating principles
and guidelines for fair data economy
• the consumers’ right to their data and its control will be strengthened
• companies will construct new kinds of value networks
• data provided by consumers/shared by companies will enable new, globally
competitive service concepts and business models to be created
• the consumers’ right to their data and its control will be strengthened

26. Current situation Future scenario 1 Future scenario 2
Current situation Future scenario 1 Future scenario 2
Data economy optimists realistically think that both possible
scenarios are full of opportunities. Data economy pessimists
don’t even understand there is anything to worry about…
There is not significant difference between the future scenarios per se , but massive
difference when looking at watershed question of competitive advantage
14%
27%
26%
33%
yes, it
already has
yes, it will in
the future
no
possibly
59%
14%
Source: Sitra Business Survey 05/2019. Question “Attitude towards data economy: Could data exchange bring competitive edge to our organisation?” n = 1654 The questions “Please evaluate what portion of
your company’s turnover digitisation and data economy is subject to business risk (business lost to competition or solutions created by digitisation)?”, “Please evaluate the effect of the data economy created by
market digitisation on your company’s business”, “Please evaluate the effect of the digitisation on your customers’ behaviour while developing your company’s customer understanding?”
In Scenario 1, the
most powerful
operators in data
economy are still
the platform
economy giants
In Scenario 2, the
playing field is
evened out by fair
data economy
practices and
regulations for the
exchange of data
and value between
companies
46,0 47,8 45,7
29,1 30,3 28,6
15% 49% 36% 46% 41%13%
49% 40%12% 46% 45%9%
21% 68% 11%
71% 16%13%
70% 18%12%
73% 15%12%
Negative Neutral Positive
42% 51%7%
41% 52%7%
73% 16%11%
68% 23%9%
Of the turnover:
at risk%
The impact of digitisation
on my own business
The impact of digitisation
on customer understanding
Of the turnover:
at risk%
The impact of digitisation
on my own business
The impact of digitisation
on customer understanding
Of the turnover:
at risk%
The impact of digitisation
on my own business
The impact of digitisation
on customer understanding
Of the turnover:
at risk%
The impact of digitisation
on my own business
The impact of digitisation
on customer understanding
Of the turnover:
at risk%
The impact of digitisation
on my own business
The impact of digitisation
on customer understanding
Of the turnover:
at risk%
The impact of digitisation
on my own business
The impact of digitisation
on customer understanding

27. Already a quarter of Dutch
companies consider themselves
to be Ecosystem drivers
24%
Sitra’s company survey 2019 in Finland, France, Germany and the
Netherlands.

28. Companies can be divided into four categories based on
customer understanding and business model
- Companiesat the top want to
control the customer interface
- Companiesat the bottom
specialise in producing
products and services for
distribution
- Companies on the left
operate as part of a value chain
- Companieson the right
operate as part of an
ecosystem
Source: ”What`s Your Digital Business Model? Six Questions to Help You Build the Next-Generation Enterprise” S Worner, P Weill, HBR Press
2018
Value chain Ecosystem
PartialPerfect
End-customerunderstanding
Business design
Omnichannel Ecosystem driver
Supplier Modular producer
• Owner of customer
relationship
• Multichannel customer
experience provider for
different life situations
• Integrated value chain
• Customers think it is the place for
a given service
• Seamlessly links other services with
their own provision
• Premium customer experience
• Collects customer data
• Charges “rent” from other operators
• Products are sold through
another supplier
• Low production costs and
incremental innovations
• Seamless connections between
supply channels
• Is able to connect to any ecosystem
• Continuous product and service
innovation
Value chain Ecosystem
Customer interface
Products and services

29. Finnish businesses are not ecosystem players
Ecosystem drivers have the highest potential to create added value and, in the
Netherlands, there are nearly twice as many of those (24%) compared to Finland (13%) as
Finnish companies position themselves as value chain players
Source: Sitra Business Survey 05/2019. Question “From the following data economy related statements, choose how well they describe your company’s current business” N=1229. Model
”What’s Your Digital Business Model? Six Questions to Help You Build the Next-Generation Enterprise” S Worner, P Weill, HBR Press 2018
47% 13%
16% 25%
Finland
29% 17%
20% 30%
Germany
31% 24%
18% 26%
Netherlands
32% 19%
18% 30%
France
Value chain Ecosystem
PartialPerfect
End-customerunderstanding
Business design
Omnichannel Ecosystem driver
Supplier Modular producer
• Owner of customer
relationship
• Multichannel customer
experience provider for
different life situations
• Integrated value chain
• Customers think it is the place for a
given service
• Seamlessly links other services with
their own provision
• Premium customer experience
• Collects customer data
• Charges “rent” from other operators
• Products are sold through
another supplier
• Low production costs and
incremental innovations
• Seamless connections between
supply channels
• Is able to connect to any ecosystem
• Continuous product and service
innovation
38%
47%49%
50%

30. Recap
1. SMEs have difficulty building competitive edge in data economy.
2. GDPR high achievers understand the value of their data repositories and
are ready to create new data-based products and services.
3. French businesses show highest interest towards the Fair Data label.
4. Those with a positive attitude towards data economy are realistic about
the threats and opportunities of the future.
5. One needs to be an ecosystem player to succeed in data economy – Dutch
companies have the lead

31. What Are the Benefits of Data
Sharing?
UnitingSupplyChainandPlatformEconomyPerspectives
Industry and Data Research Project
Timo Seppälä
19.09.2019

32. 20.9.2019
32
How has data sharing emerged
between companies?
What types of benefits have companies
reached by sharing data?
Source: Huttunen, Seppälä, Lähteenmäki & Mattila, 2019

33. Transformation:
How has data sharing emerged between companies?
20.9.2019
33
Source: Huttunen, Seppälä, Lähteenmäki & Mattila, 2019

34. 20.9.2019
34
Data sharing is a
common business
practice for 49% of
companies
Source: Huttunen, Seppälä, Lähteenmäki & Mattila, 2019

35. Typology of Data Platforms
20.9.2019
35
• Propriatory data (Company)
– Company internal use only data repository. Access to data maintaned by the
company
• Inner circle data (Platform)
– Shared data repositories. Access to data maintained collectively with boundary
resources.
• Distributed data (Industry)
– Controlled by a third-party actor. Shared practices and technology to access and
share information.
• Open data (Open)
– Distributed, accessible by publicly auditable rules. Programmable interfaces as a
key boundary resource.
Source: Rajala, Hakanen, Mattila, Seppälä & Westerlund, 2018

36. Transformation:
Categorization of identified data-related benefits
20.9.2019
36
Source: Huttunen, Seppälä, Lähteenmäki & Mattila, 2019
Operational
perspective of
data sharing
benefits well
understood by
the companies.

37. From Supply Chains to Platforms
20.9.2019
37
• Operational Data Sharing
– (e.g. Operations and Research & Development data)
• NEW: Markets Data Sharing (Customer)
– (e.g. Customer data)
Source: Huttunen, Seppälä, Lähteenmäki & Mattila, 2019

38. Markets Data Sharing
20.9.2019
38
Key Drivers:
1. The Fragmentation of Customer Requirements
2. Opportunity for new types of (mostly unknown)
externalities
Source: Seppälä, Niemi, Pajarinen, Lähteenmäki & Mattila, Forthcoming, 2019

39. Model terms of the technology industries
for data sharing
20.9.2019
39
• Propriatory information
• Confidential information
• Distributed information
• Open information
Source: Teknologiateollisuus, 2019

40. Transformation:
Categorization of identified data-related
benefits
20.9.2019
40
Source: Huttunen, Seppälä, Lähteenmäki & Mattila, 2019
Strategic
perspective of
data sharing
opportunities are
not understood
by the
companies.

41. Why companies are not moving forward?
20.9.2019
41
The tools for evaluating the value
capture of new types of externalities
is missing from widely accepted
business case valuation methods.
Source: Huttunen, Seppälä, Lähteenmäki & Mattila, 2019

42. What are your data sharing and
categorization strategies?

43. 20.9.2019
43
What type of data resources
(information resources) can companies
treat as proprietary, confidential,
distributed or as open?

44. How to get going with
the paperwork – data
economy rulebook at
your service
Jyrki Suokas

45. Data Ecosystem Rulebook
- Ecosystem Rulebook is the founding document that members of
a data ecosystem sign to adhere to
- Rulebook helps the ecosystem orchestrator to create the
rulebook together with its ecosystem partners
- Rulebook template contains a set of control questions that drive
the results to fill the rulebook section by section:
1. Business – What is the vision and mission for the ecosystem. What are
the business models for all participants in the ecosystem. Also terms
on which new participants can be taken onboard
2. Technical – what technical means (data formats, consent
management, logging etc.) are used
3. Legal – How different legislations enable or inhibit the activities in the
ecosystem.
4. Data – different laws and regulations on different kind of data
5. Ethical – how data is sourced and how services utilize data. ow
ecosystems thrive from sustainable and fair use of data. What kind of
values ecosystems have
45
Multiple bilateral agreements
Rulebook

46. Objective
- To create a common rulebook model with a base structure for different data
ecosystems
– Making it easier and cost efficient to create an ecosystem rulebook
– Making it possible for companies and organisations to join various data ecosystems more
easily
– Increasing know-how, trust and common market practises in the market
– Ensuring fair, sustainable and ethically business within the data ecosystems
- To build a tool that helps different data ecosystems to utilize a common
rulebook structure and a process where by answering various modular
control questions, to create make a initial version of the data ecosystem
specific rulebook. The initial rulebook is then finalised by experts.
46

47. Current state
- Rulebooks are hand written by expensive experts – lawyers, business developers and IT
architects - who start from scratch each time a new rule book needs to be written
- Very little or no reuse
- Extra iterations are costly because these expensive experts are involved in both
preparation and finalization phases
Preparation Finalization
47

48. Near future state
- Preparation phase is separated from Finalization phase by creating an initial list of the
control questions. Business leaders go through the list and by answering the questions
respective sections in the rulebook structure template are filled with answers.
- This creates the initial rulebook which the experts then finalize
- Iterations in the Finalization phase are reduced
Preparation Finalization
48

49. End state
- A tool which guides the business leader to go through the control questions. Tool
automates the creation of the initial rulebook as much as possible
- Control questions and rulebook structure are stored in updateable data repository.
- Iterations in the Finalization phase are minimized
Preparation Finalization
49

50. Rulebook interoperability
- Rulebook interoperability
validation process ensures
that the resulting
rulebooks conform to set
quality and content
standards
- This also ensures
interoperability between
data ecosystems
50

51. Technology
Business
Ethics
Legal System
Data Network – Rulebook
General Part
- ”sales brochure”
Check List
- Control Questions
Parties
PartiesParties
- members
Roles
Externals:
- Individuals
- Legal entities
- others Terms
Data
Sets
Code of Conduct
Agreement
Glossary
Specific Terms
General Terms
Accession Agmt
Business
Annex
Tech
Annex

52. Approach validation
- Approach process is being tested against past, present and future rulebook work to
ensure that the approach is valuable enough according to 80/20 rule
Already completed rulebooks
RETRO
Rulebooks in progress
REQUIREMENTS
Future Rulebooks
DIRECTION
Past RB1
Past RB2
Current RB1
Current RB2
Future RB1
Future RB2
Future RB3
Future RB4
52

53. Plan to Publish the First Version of the
Reference Rulebook
- In the next two months (09/2019-10/2019):
– Facilitation team will update the General Part and draft the next version of the Check List / Control
Questions
– Legal team will draft the first version of the General Terms of the Agreement
– The Ethics Team will draft the Code of Conduct
– Business Team will work on the business model and capability approach
– Rulebook Work Group will meet, discuss the drafts and give feedback bi-weekly
- The first version of the Rulebook including the above mentioned parts will be
publishable in November 2019.

54. Rulebook Next Steps after November Launch
- Current working group will continue to work on enhancing the control questions and
rulebook structure based on real world feedback
- Additional members will be invited into the working group
- Tool creation will commence after baseline has been stabilized
54

55. Thank you!
#IHAN
#fairdataeconomy
#NDERainmakers