Transcript
Page 1: ICT-enablement of Minimum Income Support - EU Seminar April 3rd 2014

1 | © 2012 Oracle Corporation – Proprietary

ICT Enablement of Minimum Income Support Schemes

High-level Member State Seminar, Brussels April 3rd, 2014

Christian Wernberg-Tougaard, Director, Social Welfare, EMEA

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The following is intended to outline our general product

direction. It is intended for information purposes only, and

may not be incorporated into any contract. It is not a

commitment to deliver any material, code, or functionality,

and should not be relied upon in making purchasing decision.

The development, release, and timing of any features or

functionality described for Oracle’s products remains at the

sole discretion of Oracle.

Safe Harbor Statement

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About me ...

• Head of Social Welfare Practice, Oracle Industry Bus. Public Sector, EMEA

• Nordic Public Sector Industry Lead

• Global Lead on Error, Fraud and Corruption (EFC)

• Macro economist (specialized in Developing Economics and Labour Economics)

• Worked with the impact of ICT on Public Sector for the last 17 years, including being:

– Senior expert for the Danish Government / Parliament on technology issues

– Member of Board of Technologies eVoting comittee.

– Expert for the European Commission (eInclusion Policy Support Program, Safer Internet for Children) and the European Parliament (RFID and Identity Management STOA).

– Different director roles in EMEA for IT-industry companies working with Business Development, Strategic Marketing, Innovation & Transformation. Worked as a Management consultant

– Head of Sector Danish Ministry of Science

• Frm. Chairman of The Danish Board for Greater IT-security

• Frm. Member of ENISA’s Permanent Stakeholder Group

Christian Wernberg-Tougaard LinkedIn: www.linkedin.com/in/christianwernbergtougaard Twitter: @digitizeSociety Blog: http://digitizesociety.blogspot.dk/ [email protected]

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Agenda

• Societal ICT Transformations Impacting Public Sector

• Focus Areas for Implementing MIS-schemes using ICT

• Recommendations

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Trends impacting Public Sector / Social Welfare

The Digital Service Society (#TDSS)

The Data & Innovation Driven Society (#TDIDS)

The CIIP Demanding Society (#TCIIPDS)

The Automated, Robot Aided Society (#TARAS)

We are creating Next-Generation of Digital Society in EU.

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Digitalization of the Social Protection Staircase* Maturity and Effectiveness!

What about Fragmentation?

Minimum Income / Social Protection Floor (ILO)

Additional Rights

Contributory

Incre

asin

g s

chem

e c

om

ple

xity

Increasing Effectiveness & Maturity of Digitalization of Social Welfare / Social Security

(*) Based on Fabio Durán-Valverde (ILO) presentation at 13th ISSA ICT conference, Brasilia, 2012 and own adds.

Social

Insurance

Funded

Own payments

to extra

pension, extra

healthcare etc.

Universal Law

Granted Rights

The Nordics

Nigeria: Mandatory

contributions from

Employers for Social

Insurance (NSITF)

Netherlands: Complex

Digitalization of Social

Security (UWV) and Old-

age Pension (SVB)

Sweden: Automated

more than 12.000 rules

for a single benefit using

OPA -> achieved 99.98%

automation; and high

convinience for citizens.

Increasing:

• Rule Complexity

• Master Data

• System

• Privacy

• Stakeholders

• TCO (Cost)?

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Social Services Solution High Level Business Process

Very MIS relevant

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Complex Rules

Objective vs

Subjective

Digital Illiteracy

Payments Digitally

Characteristics of MIS-schemes: an ICT view!

National Differences Rules/Policies

•These variates between MS – not the processes.

•Hence a uniform system with individual rules, handle the complexities of peoples’ changes of circumstances.

ICT

•Especially among the target group its difficult to understand the rules

•Right people gets the right (financial) support they are eligible for at the right time.

Digital Inclusion Citizens

•Especially among the target group its difficult to understand the rules

•In Canada its estimated that 80% of Social Welfare recipients are digital illiterates

ICT

•Enabling Assistance Centers

•Provide Screening/Application via Smart Phone Apps.

•Empowered PVP (Public Volunteer Partnership)

• Social Media Awareness Rai.

Automation / STP Schemes subjective

• Subjectivity makes it difficult to ”compute”

• Transparancy and efficiency provided by objective rules – OGP.

ICT

•Adress ”Digital ready Law-making” (end-to-end).

• Subjective rules can be transformed to objective.

Digital Payments Gov. Pay. oldfashion

• Kenya more advanced than EU average (Mpesa).

•The poor / homeless are often not allowed banking

ICT

•Ecosystem that enables poor to access/spend MIS

•Ensure functionality alternativ/digital payment (barcode for food),

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Complex Rules

Objective vs

Subjective

Digital Illiteracy

Payments Digitally

Characteristics of MIS-schemes: an ICT view!

National Differences Rules/Policies

•These variates between MS – not the processes.

•Hence a uniform system with individual rules.

ICT

•Especially among the target group its difficult to understand the rules

Digital Inclusion Citizens

•Especially among the target group its difficult to understand the rules

•In Canada its estimated that 80% of Social Welfare recipients are digital illiterates

ICT

•Enabling Assistance Centers

•Provide Screening/Application via Smart Phone Apps.

•Empowered PVP (Public Volunteer Partnership)

• Social Media Awareness Rai.

Automation / STP Schemes subjective

• Subjectivity makes it difficult to ”compute”

• Transparancy and efficiency provided by objective rules – OGP.

ICT

•Adress ”Digital ready Law-making” (end-to-end).

• Subjective rules can be transformed to objective.

Digital Payments Gov. Pay. oldfashion

• Kenya more advanced than EU average (Mpesa).

•The poor / homeless are often not allowed banking

ICT

•Ecosystem that enables poor to access/spend MIS

•Ensure functionality alternativ/digital payment (barcode for food),

•In Sweden eligibility to the

Dental Benefit is contingent on

evaluation of more than 12.000

lines of policy/rules. Automated

this takes 1-2 seconds (com-

pared to up to 4 weeks) and

99.98% is automated.

•In Denmark around 25% of

population is functional illiterates

– why self-service is difficult.

• New instruments – like video-

self-service kiosks – helps

empower the poor/homeless.

•New Zealand (Te Tari Taake) is

leading on using ICT to enable

holistic connectivity between

”Idea->Law->ICT enablement”.

• A requirement to enable STP is

good master data management

– eg. UWV in Netherlands.

•Ireland – DSP – is currently

evaluating how to operate a

sophisticated ePayment system.

•Denmark is enabling homeless

with ”payment” through

NemKonto or ”Citizens service”

– latter might be stigmatizing.

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Challenge – digitalization of subjectivity (human interaction).

• A 100% subjective evaluation of ”fit” with rules and policies gives risk for citizens to be treated unequal -> rule of law issue. Denmark has a principle of not allowing ”evaluation/judgement” to be put under ”rule”.

• To support caseworkers doing ”human evaluation” requires strong knowledge sharing (what did others do in similar cases) and exact information on the individual (Best in Class Master Data).

• Automation can be achieved by incorporating digitalization thinking when drafting the legislation / policy in order to ensure ”non-interpretation” rules and master data consistancy.

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Technology Innovation: Policy Automation

Separating Processes and Rules makes Administrations much more agile.

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Recommendations for MIS-schemes and ICT

Always Use COTS. No Custom Coding. Let Business

do the Business.

Use Natural Language Rule Engines. Let Business do the

Business.

EU Cloud for Cross MS Eligibility Determination

Examine Payment options for the citizens. And ensure

assisted self-service

Enable Transparancy of Determination Path

Ensure automation/STP. Always humans behind

For effective solutions, Member States and The EU Commission should consider:

The 80/20 Rule still apply (80% Organisation and 20% Technology)

No-one can eat a whole Elephant in one bite.

Create implementation dialog between Customer, Implementer and Vendor.

Establish good master-data, as they form the foundation for correct determinations.

IMP

LE

ME

NT

AT

ION

BE

ST

PR

AC

TIS

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