EcoKnow: Effektiv, Compliant og samskabt digitalisering af vidensarbejde

Effective
co-created &
compliant adaptive case management for
Know-ledge workers
Roald Als
Thomas Hildebrandt
Associate Professor
IT University of Copenhagen
Inﬁnit Seminar
Processes & IT
Århus, November 2nd, 2017
Grand Solutions

EcoKnow Presentation - Infinit Seminar - Nov 2nd Thomas Hildebrandt, hilde@itu.dk
IT UNIVERSITY OF COPENHAGEN
A single slide about me
• 2000: PhD in computer Science, Århus University
• 1999-: Researcher & teacher at IT University of
Copenhagen (ITU) in “digitalisation of processes”
• 2007-: Head of research & innovation projects in
collaboration with Microsoft, Resultmaker,
Exformatics, BaneDanmark, DSB, KL, BRFkredit,…
• 2012 - Head of research group at ITU, interest
groups for digitalisation within infinit.dk, cfir.dk and
videndanmark.dk and private digitalisation consultant
2

Digitalised Case Management
3
RPA
BPM
Case Worker
Goal: Effectiveness and higher quality

Towards automation?
4
~27% of all tasks in public
services in DK potentially
automatable
A FUTURE
THAT WORKS:
the impact of automation
in Denmark
A STRONGER AND
MORE SECURE
DIGITAL DENMARK
Digital Strategy
2016-2020
The Government /
Loca Government Denmark /
Danish Regions /
Effective & trustworthy digital
public services, freeing case
workers from routine tasks &
exploiting data to improve
processes to the beneﬁt of citizens

Today: Procedural automation
5
diagnosis phase, the operational processes are analyzed to identify
to ﬁnd things that can be improved. The focus of traditional work-
ment (systems) is on the lower half of the life-cycle. As a result there
t for the diagnosis phase. Moreover, support in the design phase is
viding an editor while analysis and real design support are missing.
Figure 13: PAIS life-cycle.
cle, we showed that PAISs support operational business processes
advances in information technology with recent insights from man-
ce. We started by reviewing the history of such systems and then
ocess design. From the many diagramming techniques available, we
icular technique (Petri nets) to show the basics. We also emphasized
of process analysis, e.g., by pointing out that 20 percent of the more
ess models in the SAP reference model are ﬂawed [24]. We also
26
Ny medarbejder
Virksomhed
FM
FM
Find plads ved
skrivebord
Skrivebords-
nummer
1 uge før første arbejdsdag
Placer PC på
bord
God første arbejdsdag
Håndtering af PC
PC type kan ikke leveres
PC type
HR
HR
Ret til PC?
kontrakter
Behov for PC?
Modtag
underskrevet
kontrakt
Arkiver kontrakt
IT Leverandør
behovforPC
Nej
Ja

5
26
Only known and predictable routes are described
Ny medarbejder
Virksomhed
FM
FM
Find plads ved
skrivebord
Skrivebords-
nummer
Placer PC på
bord
Håndtering af PC
PC type
HR
HR
Ret til PC?
kontrakter
Behov for PC?
Modtag
underskrevet
kontrakt
Arkiver kontrakt
IT Leverandør
behovforPC
Nej
Ja

5
26
Ny medarbejder
Virksomhed
FM
FM
Find plads ved
skrivebord
Skrivebords-
nummer
Placer PC på
bord
Håndtering af PC
PC type
HR
HR
Ret til PC?
kontrakter
Behov for PC?
Modtag
underskrevet
kontrakt
Arkiver kontrakt
IT Leverandør
behovforPC
Nej
Ja
Introduce unnecessary dependencies
IT UNIVERSITY OF
Towards effective, ﬂexible & legally compliant digital knowledge workﬂows ITU, Se
Thomas T. Hildebrandt (hilde@itu.dk)
The computer says no….
5
Performance
goals
Best
practice
the computer
says no
The baby is
coming!

5
26
Ny medarbejder
Virksomhed
FM
FM
Find plads ved
skrivebord
Skrivebords-
nummer
Placer PC på
bord
Håndtering af PC
PC type
HR
HR
Ret til PC?
kontrakter
Behov for PC?
Modtag
underskrevet
kontrakt
Arkiver kontrakt
IT Leverandør
behovforPC
Nej
Ja
Only describe the procedure (how), not why
IT UNIVERSITY OF
5
Performance
goals
Best
practice
the computer
says no
The baby is
coming!

5
26
Ny medarbejder
Virksomhed
FM
FM
Find plads ved
skrivebord
Skrivebords-
nummer
Placer PC på
bord
Håndtering af PC
PC type
HR
HR
Ret til PC?
kontrakter
Behov for PC?
Modtag
underskrevet
kontrakt
Arkiver kontrakt
IT Leverandør
behovforPC
Nej
Ja
Only describe the procedure (how), not why
IT UNIVERSITY OF
5
Performance
goals
Best
practice
the computer
says no
The baby is
coming!
Difﬁcult to maintain and update when
regulations and best practice changes

arbejdsgangsbanken.dk
6
• Lov om Aktiv beskæftigelsesindsats
(LBK nr 1428 af 14/12/2009)
• Lov om Aktiv socialpolitik
(LBK nr 946 af 01/10/2009)
• Lov om Arbejdsløshedsforsikring
(LBK nr 574 af 27/05/2010)
• Lov om Integration af udlændinge
(LBK nr 1062 af 20/08/2010)
• Lov om Sygedagpenge
(LOV nr 563 af 09/06/2006)
• Retssikkerhedsloven
(LBK nr 1054 af 07/09/2010)
• Datagrundlag
(BEK nr 418 af 23/04/2010)
Compliant?
2010: Case Studies of
Best Practice
Workﬂow and
Workﬂow in Practice
(Innovation Network Project)

6
(LBK nr 1428 af 14/12/2009)
(LBK nr 946 af 01/10/2009)
(LBK nr 574 af 27/05/2010)
(LBK nr 1062 af 20/08/2010)
(LOV nr 563 af 09/06/2006)
(LBK nr 1054 af 07/09/2010)
• Datagrundlag
(BEK nr 418 af 23/04/2010)
Change in law!
Compliant?
Best Practice
Workﬂow and

6
(LBK nr 1428 af 14/12/2009)
(LBK nr 946 af 01/10/2009)
(LBK nr 574 af 27/05/2010)
(LBK nr 1062 af 20/08/2010)
(LOV nr 563 af 09/06/2006)
(LBK nr 1054 af 07/09/2010)
• Datagrundlag
(BEK nr 418 af 23/04/2010)
Change in law! Process change??
Compliant?
Best Practice
Workﬂow and

6
(LBK nr 1428 af 14/12/2009)
(LBK nr 946 af 01/10/2009)
(LBK nr 574 af 27/05/2010)
(LBK nr 1062 af 20/08/2010)
(LOV nr 563 af 09/06/2006)
(LBK nr 1054 af 07/09/2010)
• Datagrundlag
(BEK nr 418 af 23/04/2010)
Compliant?
Best Practice
Workﬂow and
Process change!

6
(LBK nr 1428 af 14/12/2009)
(LBK nr 946 af 01/10/2009)
(LBK nr 574 af 27/05/2010)
(LBK nr 1062 af 20/08/2010)
(LOV nr 563 af 09/06/2006)
(LBK nr 1054 af 07/09/2010)
• Datagrundlag
(BEK nr 418 af 23/04/2010)
Compliant?
Best Practice
Workﬂow and
Process change!
Still compliant?

The Process Spectrum
7

7
Completely predictable
Highly repetitive & objective
e.g. preparing a meeting,
handling routine application

7
Completely unpredictable
Little repetitive,
explorative, unknown rules
e.g. visiting a family for
the first time

7
Little repetitive,
the first time
Partially predictable,
repetitive but varying routes
following known rules
e.g. handling application for
economic support

7
Little repetitive,
the first time
economic support
Business Process Management (BPM)
Robotic Process Automation (RPA)

7
Little repetitive,
the first time
economic support
Electronic Case &
Document Management (ESDH)

7
Little repetitive,
the first time
economic support
Electronic Case &
Document Management (ESDH)“Fagsystemer”

Ex: Child with disabilities
1. Parents discover child has a permanent disabilities that
causes extra expenses (e.g. special equipment in house)
2. Parents apply for economic support (§ 41)
3. Parents need to reduce working time and receive
compensation (§ 42)
4. Parents get extra help some days a month (§ 84)
5. Child turns 18 and case changes to adult regulations
8

Challenges today
• It-support only for some activities (e.g. payments)
• No standard way of recording the case history
• Limited support for navigating the law
• Limited systematic sharing and use of knowledge
• The law changes
• The case worker changes
• The needs of the citizens changes
9

The Core Idea
Rigid Procedural Business
Process Management Systems
“the computer says no
(or leaves you on your own)”
Flexible Prescriptive Declarative
Adaptive Case Management
“the computer says why
and guides you on the way”

Key research questions
• How can we digitalise the law such that it can be
maintained effectively and support case management?
• How can we gather and use data to help both
citizens and case workers to ﬁnd the best route?
11
Exformatics
KMD
MAPS (Italy)
Copenhagen
University
DTU
David Basin, ETH Zurich, Switzerland
Institute of information Security
Marlon Dumas & Fabrizio Maria Maggi,
University of Tartu, Estonia
Hajo Reijers, VU University, Amsterdam
Municipality partners
as early adopters:
Koncern IT - Copenhagen Municipality
IT & Digitalisation,
Syddjurs Municipality
Kammeradvokaten
& Globeteam
Enabling technologies
shared as open source tools
via the OS2 open source
digitalisation community
Flexibility
Ef
adap
decision
support
Joos Buijs, Eindhoven Data Science Center
The Netherlands
taly)
as early adopters:
Kammeradvokaten
& Globeteam
ss and legal compliance
Flexibility
Effective, co-created & compliant
adaptive case management solutions
for knowledge workers
decision
support
er
tion of jobs outside the Cph region, increase SME’s use of ICT for di
ase the share of e-commerce directed to Danish shops: The statistic
014 show that nordic consumers shopped in total for 8,31 billion DKK
ries while 70% of the Danish consumers did shop on the internet, a
s went to e-shops outside Denmark. With the strong consortium, inte
and timely objectives, it is anticipated that U-CAPACITY will have a
n all the involved research disciplines and more-over participate sign
ncreasing digitalization of work processes in the Danish industry.
Exformatics
KMD
MAPS (Italy)
Switzerland
as early adopters:
Kammeradvokaten
& Globeteam
EcoKnow: Effective, co-created & compliant
adaptive case management for knowledge workers
Need for adaptable digitalisation of knowledge work processes
Changing National and EU regulations (e.g. data protection)
Increased effectiveness and legal compliance
01.10.2017 30.09.2021
nk
itzerland
curity
ia Maggi,
onia
msterdam
as early adopters:
& Globeteam
Flexibility
decision
support
ence Center
Figur 1
Side/Page 22 af/of 73

Key methods & disciplines
• Field studies of work practices and research in
computer supported cooperative work (ITU & KU)
• Data & process mining for predictive and prescriptive
process management (ITU, KU & KMD)
• Formal models of law and processes (ITU &
Exformatics)
• Understandability studies of modelling tools and
methods (DTU & KU)
12

Predictive Process Management
13
event logs
$$$$$$$$$$$$$$$$$$$$
n)på)det)finansielle)verdenskort,$Copenhagen$2009:$
/Dokumenter/Københavnpådetfinansielleverdenskort.aspx$$
al$vækst,$ANBEFALINGER,$Januar$2014$$p.$31ff$Anbefaling)#3.)Et)nationalt)partnerskab)skal
& Fabrizio Maria Maggi,
of Tartu, Estonia
University, Amsterdam Syddjurs Municipality
Flexibility
decision
support
oven Data Science Center
Netherlands
Fi
Outcomes
Knowledge work GPS

Predictive Process Management
13
event logs
$$$$$$$$$$$$$$$$$$$$
n)på)det)finansielle)verdenskort,$Copenhagen$2009:$
/Dokumenter/Københavnpådetfinansielleverdenskort.aspx$$
al$vækst,$ANBEFALINGER,$Januar$2014$$p.$31ff$Anbefaling)#3.)Et)nationalt)partnerskab)skal
& Fabrizio Maria Maggi,
of Tartu, Estonia
University, Amsterdam Syddjurs Municipality
Flexibility
decision
support
oven Data Science Center
Netherlands
Fi
Outcomes
How to predict the
outcome
given a partial trace
of events?
Knowledge work GPS

Business Processes
14

Business Processes
14
(LBK nr 1428 af 14/12/2009)
(LBK nr 946 af 01/10/2009)
(LBK nr 574 af 27/05/2010)
(LBK nr 1062 af 20/08/2010)
(LOV nr 563 af 09/06/2006)
(LBK nr 1054 af 07/09/2010)
• Datagrundlag
(BEK nr 418 af 23/04/2010)

Events
15
case id: CPR of citizen + case name
data attributes: e.g. key ﬁgures in report
1 = [(consultation, 1, 10:30AM, (age, 33), (gender, female), (amountPaid, 10), (department, radiotherapy)) . . .
(ultrasound, 1, 10:55AM, (age, 33), (gender, female), (amountPaid, 15), (department, NursingWard))]
2 = [(order blood, 2, 12:30PM, (age, 56), (gender, male), (department, GeneralLab) . . .
(payment, 2, 2:30PM, (age, 56), (gender, male), (amountPaid, 100), (deparment, FinancialDept))]
Fig. 1: Extract of an event log.
Example: Jobcenter in municipality
Example: Hospital
An event have an activity name, a case id, a time-stamp and
possibly some additional data attributes
Challenges: events distributed in many systems or not recorded
name, case-id, time & data often not clear from logs

Traces & outcomes
16
Traces are ﬁnite sequences of events for the same case
Outcome function maps traces to outcomes
(may have several outcome functions)

Trace Encoders & Features
17
Number of cancelations, geographic area -
i.e. the “shape” and characteristics of path
Trace encoders map partial traces to
ﬁnite set of features
Challenges: What are the right features?
Which features are ethical/fair to use ?
How to effectively extract features?
Can features be identiﬁed automatically ?

Classifiers
18
(Known as early sequence classification)
Classifiers map features to outcome predictions
Challenges: How to effectively train classifiers?
How to explain predictions? How to use them?
Features
Trace encoder
outcome
classification

Process mining
19
Log ﬁles
https://youtu.be/7oat7MatU_U

Process mining
19
Log ﬁles
Statistically inferred process ﬂow diagram

Process mining
19
Log ﬁles
Mining used for discovery, analysis, prediction, prescription
Statistically inferred process ﬂow diagram

Mined diagrams often too complex
20
If the log has a lot of variation
the mined process quickly gets a
complex spaghetti diagram

20
Failure to recognise concurrency

20
Failure to recognise concurrency
Inability of process language to
represent variation in a concise way

Declarative Process Mining
21
Declarative Process Mining for DCR Graphs⇤
Søren Debois
Copenhagen, Denmark
debois@itu.dk
Thomas T. Hildebrandt
Copenhagen, Denmark
hilde@itu.dk
Paw Høvsgaard Laursen
Copenhagen, Denmark
pawh@itu.dk
Kenneth Ry Ulrik
Copenhagen, Denmark
kulr@itu.dk
ABSTRACT
We investigate process mining for the declarative Dynamic
Condition Response (DCR) graphs process modelling lan-
guage. We contribute (a) a process mining algorithm for
DCR graphs, (b) a proposal for a set of metrics quantifying
output model quality, and (c) a preliminary example-based
comparison with the Declare Maps Miner. The algorithm
takes a contradiction-based approach, that is, we initially
assume that all possible constraints hold, subsequently re-
moving constraints as they are observed to be violated by
traces in the input log.
Keywords
Declarative process mining; DCR graphs
1. INTRODUCTION
Business process management (BPM) technologies [33]
support the management and digitalisation of workflows and
business processes by employing explicit process models, fol-
lowing a cycle of process (re)design, validation, execution
and monitoring.
Process mining algorithms [32] have been proposed for the
identification of process models from process logs, support-
ing both process design and compliance monitoring.
Most industrial BPM tools and process miners describe
processes as imperative flow diagrams such as BPMN. How-
ever, flow diagrams tend to get either too rigid or too com-
plex, in particular for knowledge work processes having a
high degree of variation [28]. Moreover, flow diagrams only
describe how to perform a process, leaving a gap to the legal
regulations and guidelines, that are often more declarative
in nature, describing why the process must be performed in
⇤Authors listed alphabetically. This work supported in part
by the Velux Foundation, grant 33295, and Exformatics
A/S.
Permission to make digital or hard copies of part or all of this work for personal or
classroom use is granted without fee provided that copies are not made or distributed
for profit or commercial advantage and that copies bear this notice and the full citation
on the first page. Copyrights for third-party components of this work must be honored.
For all other uses, contact the owner/author(s).
SAC 2017 April 03-07, 2017, Marrakech, Morocco
c 2017 Copyright held by the owner/author(s).
ACM ISBN 978-1-4503-4486-9/17/04.
DOI: http://dx.doi.org/10.1145/3019612.3019622
certain ways, not how exactly it must be performed. For
instance, a clinical guideline may state, that a patient must
consent to a blood transfusion [13]. It does not state ex-
actly when such consent should be obtained, only “prior to
the transfusion”.
For this reason, it is recommended to use flow diagrams
only for routine processes, or for describing common stan-
dard practices and allow deviations [28]. It has been advo-
cated that declarative notations should be used as output of
process mining (e.g. [17]) and for run-time process support
(e.g. [25, 24, 29]). For the former, one hopes to extract
from a process log the rules obeyed in practice (the “why”)
as opposed to a flow-diagram describing the usual executions
(the “how”). For the latter, one hopes to guide knowledge
workers to activities in conformance with rules and regula-
tions.
Implementation techniques for most declarative models
such as Declare [27] and DecSerFlow [31], rely on translating
the declarative constraints to an imperative model (e.g., an
automaton [20]) to enable execution. Such translation usu-
ally entail a state-space explosion, and run-time adaptation
of constraints becomes more di cult, because the automa-
ton must be recomputed when constraints change.
A notable exception is the Dynamic Condition Response
(DCR) graphs process language [11, 30]. DCR graphs can be
executed without intermediate transformation to an imper-
ative model creating the entire transition graph, and more
directly support run-time adaptive case management [24,
5]. DCR graphs are supported by industrial design and case
management tools (see e.g. dcrgraphs.net and [5]).
In the present paper, we present the first process mining
algorithm for DCR graphs.
2. DCR GRAPHS
In this Section, we briefly recall DCR graphs. For a formal
introduction and applications, refer to [11, 23, 30, 3, 5, 6].
Dynamic Condition Response graphs is a declarative mod-
elling notation describing at the same time a process and
its run-time state. The core notation comprises activities,
activity states, and four relations between activities. An ac-
tivity state comprises three booleans, indicating respectively
whether the activity has been executed, is included, and
is pending. Intuitively, activities that are not included are
treated as temporarily absent from the workflow; activities
that are pending must eventually be executed or excluded
before the workflow may complete.
Presented for BPMEA track at 32nd ACM SAC 2017
condition response
Hypothesis: Constraints can be used as features
real-time mining can be used as encoding

Declarative Process Mining
21
Statistically inferred process constraints
Declarative Process Mining for DCR Graphs⇤
Søren Debois
Copenhagen, Denmark
debois@itu.dk
Thomas T. Hildebrandt
Copenhagen, Denmark
hilde@itu.dk
Paw Høvsgaard Laursen
Copenhagen, Denmark
pawh@itu.dk
Kenneth Ry Ulrik
Copenhagen, Denmark
kulr@itu.dk
ABSTRACT
We investigate process mining for the declarative Dynamic
Condition Response (DCR) graphs process modelling lan-
guage. We contribute (a) a process mining algorithm for
DCR graphs, (b) a proposal for a set of metrics quantifying
output model quality, and (c) a preliminary example-based
comparison with the Declare Maps Miner. The algorithm
takes a contradiction-based approach, that is, we initially
assume that all possible constraints hold, subsequently re-
moving constraints as they are observed to be violated by
traces in the input log.
Keywords
Declarative process mining; DCR graphs
1. INTRODUCTION
Business process management (BPM) technologies [33]
support the management and digitalisation of workflows and
business processes by employing explicit process models, fol-
lowing a cycle of process (re)design, validation, execution
and monitoring.
Process mining algorithms [32] have been proposed for the
identification of process models from process logs, support-
ing both process design and compliance monitoring.
Most industrial BPM tools and process miners describe
processes as imperative flow diagrams such as BPMN. How-
ever, flow diagrams tend to get either too rigid or too com-
plex, in particular for knowledge work processes having a
high degree of variation [28]. Moreover, flow diagrams only
describe how to perform a process, leaving a gap to the legal
regulations and guidelines, that are often more declarative
in nature, describing why the process must be performed in
⇤Authors listed alphabetically. This work supported in part
by the Velux Foundation, grant 33295, and Exformatics
A/S.
Permission to make digital or hard copies of part or all of this work for personal or
classroom use is granted without fee provided that copies are not made or distributed
for profit or commercial advantage and that copies bear this notice and the full citation
on the first page. Copyrights for third-party components of this work must be honored.
For all other uses, contact the owner/author(s).
SAC 2017 April 03-07, 2017, Marrakech, Morocco
c 2017 Copyright held by the owner/author(s).
ACM ISBN 978-1-4503-4486-9/17/04.
DOI: http://dx.doi.org/10.1145/3019612.3019622
certain ways, not how exactly it must be performed. For
instance, a clinical guideline may state, that a patient must
consent to a blood transfusion [13]. It does not state ex-
actly when such consent should be obtained, only “prior to
the transfusion”.
For this reason, it is recommended to use flow diagrams
only for routine processes, or for describing common stan-
dard practices and allow deviations [28]. It has been advo-
cated that declarative notations should be used as output of
process mining (e.g. [17]) and for run-time process support
(e.g. [25, 24, 29]). For the former, one hopes to extract
from a process log the rules obeyed in practice (the “why”)
as opposed to a flow-diagram describing the usual executions
(the “how”). For the latter, one hopes to guide knowledge
workers to activities in conformance with rules and regula-
tions.
Implementation techniques for most declarative models
such as Declare [27] and DecSerFlow [31], rely on translating
the declarative constraints to an imperative model (e.g., an
automaton [20]) to enable execution. Such translation usu-
ally entail a state-space explosion, and run-time adaptation
of constraints becomes more di cult, because the automa-
ton must be recomputed when constraints change.
A notable exception is the Dynamic Condition Response
(DCR) graphs process language [11, 30]. DCR graphs can be
executed without intermediate transformation to an imper-
ative model creating the entire transition graph, and more
directly support run-time adaptive case management [24,
5]. DCR graphs are supported by industrial design and case
management tools (see e.g. dcrgraphs.net and [5]).
In the present paper, we present the first process mining
algorithm for DCR graphs.
2. DCR GRAPHS
In this Section, we briefly recall DCR graphs. For a formal
introduction and applications, refer to [11, 23, 30, 3, 5, 6].
Dynamic Condition Response graphs is a declarative mod-
elling notation describing at the same time a process and
its run-time state. The core notation comprises activities,
activity states, and four relations between activities. An ac-
tivity state comprises three booleans, indicating respectively
whether the activity has been executed, is included, and
is pending. Intuitively, activities that are not included are
treated as temporarily absent from the workflow; activities
that are pending must eventually be executed or excluded
before the workflow may complete.
Presented for BPMEA track at 32nd ACM SAC 2017
condition response
Hypothesis: Constraints can be used as features
real-time mining can be used as encoding

Key methods & disciplines
• Field studies of work practices and research in
computer supported cooperative work (ITU & KU)
• Data & process mining for predictive and prescriptive
process management (ITU, KU, KMD)
• Formal models of law and processes (ITU,
Exformatics)
• Understandability studies of modelling tools and
methods (DTU & KU)
22

Example: Resourceforløb
• “Stk. 3. Forud for visitation til et ressourceforløb skal den
forberedende del af rehabiliteringsplanen, jf. § 30 a, være udarbejdet
og sagen have været forelagt rehabiliteringsteamet, jf. §§ 9-12 i lov
om organisering og understøttelse af beskæftigelsesindsatsen m.v.

• Beskriver:  
- aktiviteter, e.g., (a) “visitationen” eller  
(b) “rehabiliteringsplanen [...] [skal] være udarbejdet”, samt  
- relationer imellem aktiviteter, e.g., “forud for [a] skal [b]”.

forberedende del af rehabiliteringsplanen, jf. § 30 a, være udarbejdet
og sagen have været forelagt rehabiliteringsteamet, jf. §§ 9-12 i lov
om organisering og understøttelse af beskæftigelsesindsatsen m.v.”

forberedende del af rehabiliteringsplanen, jf. § 30 a, være
udarbejdet og sagen have været forelagt
rehabiliteringsteamet, jf. §§ 9-12 i lov om organisering og
understøttelse af beskæftigelsesindsatsen m.v.”

“The isomorphism principle”

forberedende del af rehabiliteringsplanen, jf. § 30 a, være
udarbejdet og sagen have været forelagt
rehabiliteringsteamet, jf. §§ 9-12 i lov om organisering og
understøttelse af beskæftigelsesindsatsen m.v.
Change

Project Organisation
Steering Partners
(ITU, KU, DTU, KMD, Exformatics)
Advisory Board
(DSC/e, TU Wien, KL, IF)
WP4: Understandability
PhD at DTU
$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$
1$Oxford$Research,$København)på)det)finansielle)verdenskort,$Copenhagen$2009:$
http://www.cfir.dk/Forside/Dokumenter/Københavnpådetfinansielleverdenskort.aspx$$
2$Vækstteam$for$IKT$og$digital$vækst,$ANBEFALINGER,$Januar$2014$$p.$31ff$Anbefaling)#3.)Et)nationalt)par
og)automatiseringen)af)særligt)små)og)mellemstore)virksomheder)betydeligt.$$
Copenhagen
University
DTU
as early adopters:
Flexibility
Effective, co-created & c
adaptive case managemen
for knowledge work
decision
support
The Netherlands
WP2: Data & Process Mining
Industry PostDoc
KMD & ITU
Nordic countries while 70% of the Danish consumers did shop on the internet, also about 70%
of the orders went to e-shops outside Denmark. With the strong consortium, international
collaboration and timely objectives, it is anticipated that U-CAPACITY will have a clearly visible
impact within all the involved research disciplines and more-over participate significantly to
the goal of increasing digitalization of work processes in the Danish industry.
$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$
2$Vækstteam$for$IKT$og$digital$vækst,$ANBEFALINGER,$Januar$2014$$p.$31ff$Anbefaling)#3.)Et)nationalt)partnerskab)skal)øge)digitaliseringen)
og)automatiseringen)af)særligt)små)og)mellemstore)virksomheder)betydeligt.$$
Municipality
Exformatics
KMD
MAPS (Italy)
Copenhagen
University
DTU
as early adopters:
Kammeradvokaten
& Globeteam
01.10.2017 30.09.2021
Flexibility
decision
support
The Netherlands
Bank
Figur 1
Contributing partners (Core-technology, validation, adoption & outreach)
R&D Work Packages:
WP3: Legal Compliance
Industry PostDoc
Exformatics & ITU
collaboration and timely objectives, it is anticip
impact within all the involved research disciplin
the goal of increasing digitalization of work pro
$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$
1$Oxford$Research,$København)på)det)finansielle)verdenskort,$Copenha
http://www.cfir.dk/Forside/Dokumenter/Københavnpådetfinansiel
2$Vækstteam$for$IKT$og$digital$vækst,$ANBEFALINGER,$Januar$2014$$p
og)automatiseringen)af)særligt)små)og)mellemstore)virksomheder)bety
Side/Page
Municipality
Exformatics
KMD
MAPS (Italy)
Copenhagen
University
DTU
Municipality p
as early ado
Koncern IT - Copenhag
IT & Digitalis
Syddjurs Muni
Kammeradvokaten
& Globeteam
EcoKnow: Effective, co-
adaptive case managemen
Enabling techno
shared as open sou
via the OS2 open
digitalisation com
01.10.2017
F
decision
support
The Netherlands
Bank
Side/Page 22 af/
WP1: Work Practices
PhD at ITU & Associate Prof at KU
challenges of process aware IT systems and usability as U-CAPACITY addresses are not only
important challenges to the financial sector, but to the society as a whole and a challenge the
Danish ICT Growth Team recommends the government and companies address to strengthen
the Danish competitiveness2
. Indeed, they estimate, that the gross value added to the Danish
businesses would be between 2,6 and 6,5 billion DKK, if the share of Danish businesses with
at least one digitalized process is increased by 1%, and states as a goal for 2020 an increase
by 10%. At the same time, the report also points to a recent study showing that the Danish
businesses are seriously lacking behind the US when it comes to use and integration of IT in
the organisation, in particular for SME’s. For ComBine in particular, U-CAPACITY contributes to
the preservation of jobs outside the Cph region, increase SME’s use of ICT for digitalization
and to increase the share of e-commerce directed to Danish shops: The statistics for first
quarter of 2014 show that nordic consumers shopped in total for 8,31 billion DKK outside the
Nordic countries while 70% of the Danish consumers did shop on the internet, also about 70%
of the orders went to e-shops outside Denmark. With the strong consortium, international
collaboration and timely objectives, it is anticipated that U-CAPACITY will have a clearly visible
impact within all the involved research disciplines and more-over participate significantly to
Municipality
Exformatics
KMD
MAPS (Italy)
Copenhagen
University
DTU
as early adopters:
Kammeradvokaten
& Globeteam
01.10.2017 30.09.2021
The Netherlands
Bank
Dissemination Collaborators:

Baseline
studies
R&D cycle 1
LAB
TRL&SRL4-5
R&D cycle 2
Relevant Env.
TRL&SRL 6-7
Evaluation
Operational Env
TRL&SRL 8
Other markets
TRL&SRL 9
The 4 WorkPackages overall follow same structure:
M6:Mar 2018 M18:Mar 2019
Agile, Situated Research & Design
Annual international workshop
Innovation conference in 2019 and 2021 (inﬁnit.dk, cﬁr.dk )
Implementation
M30:Mar 2020Sept 2017 M42:Mar 2021
Aug 2021
KMD A/S
Eskil Thygesen, Business Line Director, KMD, 49 years.
.
Education.
Mannaz Executive Leadership Education (VL), 2012.
KMD A/S
Products
releases

Success Criteriadigitalisation services.
The value created for citizens is the experienced and actual quality effectiveness and
compliance of the case processing, which will be measured by
1) questionnaires to the experienced quality of case management before and after
the introduction of EcoKnow technology,
2) reducing the number of complaints by citizens to Ankestyrelsen5
that leads to a
change of decision
3) reducing of the wasteful waiting time
The success criterion is to achieve at least 15% increase in quality on all these
measures.
The value created for case workers and municipalities is (in addition to the value
created for the citizens) the increased experienced quality and actual effectiveness of
the case management process, measured by
2) reduction of time by case workers spend on routine tasks
3) the experienced and actual ability of case workers and lawyers to efficiently on
their own digitalise and continuously adapt digitalised legal regulations and best
practice workflows, utilising sharing between case workers within and across
municipalities
4) reduction in the cost of adaptation of digitalised work processes in response to
changing requirements.
The success criterion is to achieve at least 15% increase in quality on the first 3 criteria
digitalisation services.
The value created for citizens is the experienced and actual quality effectiveness and
compliance of the case processing, which will be measured by
2) reducing the number of complaints by citizens to Ankestyrelsen5
that leads to a
change of decision
3) reducing of the wasteful waiting time
The success criterion is to achieve at least 15% increase in quality on all these
measures.
The value created for case workers and municipalities is (in addition to the value
created for the citizens) the increased experienced quality and actual effectiveness of
the case management process, measured by
2) reduction of time by case workers spend on routine tasks
3) the experienced and actual ability of case workers and lawyers to efficiently on
their own digitalise and continuously adapt digitalised legal regulations and best
practice workflows, utilising sharing between case workers within and across
municipalities
4) reduction in the cost of adaptation of digitalised work processes in response to
changing requirements.
The success criterion is to achieve at least 15% increase in quality on the first 3 criteria
and an increase of at least 50% for the last.

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$
2
Municipality
Exformatics
KMD
MAPS (Italy)
Copenhagen
University
DTU
as early adopters:
Kammeradvokaten
& Globeteam
01.10.2017 30.09.2021
Flexibility
decision
support
The Netherlands
Bank
Figur 1
1.09.2017 30.08.2021
Please contact me if you want to know more/get involved!

EcoKnow: Effektiv, Compliant og samskabt digitalisering af vidensarbejde

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