Decision Making in Public Administrations based on Analysable Process Models

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Decision Making in Public Administrations based
on Analysable Process Models

• 5th Eastern Europian eGov Days
• Prague 2007-04-13

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Current Problems in Public Administrations

• Increased service level demand from
  citizens/companies
• Decreasing tax revenue and reduced financial
  budget
• ? Need for higher process efficiency (time/cost
  savings)
• Current activities for process improvement
• Focus only on optimisation of single processes
• No over-all view on the process landscape
• Potential due to process similarities remains
  unexploited
• ? Decision makers have no profound knowledge of
  their entire process landscape

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Process modelling

• Traditional Modelling Approaches
• Use of generally applicable modelling languages
• Not domain specific (harder to understand)
• High/varying level of detail (required?)
• High degree of freedom (difficult to analyse)
• Syntactically complex (requires expert knowledge)
• Time consuming

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Process modelling

• Goals of the PICTURE-Approach
• Caputering the entire process landscape of a
  public administration
• Destributed modelling / direct involvment of
  domain experts
• Domain specific language constructs
• Simple syntactically rules (easy to learn)
• Predefined level of detail
• Comparabillity of process models
• Uncomplicated access to process information for
  futher analysis

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The PICTURE-Approach

• Model Use the Process Landscaping Module to
  capture your administrational processes including
  all necessary attribute values
• Analyse Create information based by
  transforming attributes to figures, aggregated
  along process categories and make the figures
  accessible via reports

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PICTURE language constructs

• 29 domain specific process buidling blocks (PBBs)
  
• Attributes to capture project specific information

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PICTURE language constructs

• Process
• Sequence of activities to perform a certain
  service
• Example issue passport, authorise building
  application
• Sub-Process
• Part of a process performed by a single
  orginisational unit
• Attributes e.g. number of cases per year
• Variant
• Alternative sequence of PBBs in a sub-process
• Frequency of different variants captured by
  percentage values

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PICTURE language constructs
Process Conduct a marriage
Sub-Process Verifying marriage (number of cases
100/year)
Orga-Unit 23
Variant 2 (20) Marriage German/Other
Nationality
Variant 1 (80) Marriage German/German
Teilprozess Antrag auf Hilfskrafteinstellung
bearbeiten
Sub-Process Prepare marriage (number of cases
100/year)
Fachbereich
Orga-Unit 63
Variante 1 (80) Finanzierung aus eigenem Etat
prüfen
Variane 1 (100) Standard Variant
Sub-process Conduct marriage ceremony (number of
cases 100/Jahr)
Orga-Unit 23
Variant 1 (100) Standard Variant
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Modelling view
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The PICTURE-Approach

• Model Use the Process Landscaping Module to
  capture your administrational processes including
  all necessary attribute values
• Analyse Create information based by
  transforming attributes to figures, aggregated
  along process categories and make the figures
  accessible via reports

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Elements of PICTURE Analysis

• Public administrations have large number of
  processes (gt 1000)
• Mechanism needed to organise and retrieve process
  landscape
• PICTURE allows for abitrary categorisation
  criteria
• Possible categorisation criterias are
• Product catalogue
• Organisational structure
• Customer group
• Type of service

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Elements of PICTURE Analysis

• Attributes are connected to figuers
• Figures are aggregated along variants,
  sub-process , processes and all defined
  categories
• Decision makers can make use of the figures in
• Ad-Hoc Queries
• Search information base on given criterias
• Aggregation level, figure, relational operator
  and compare value
• Reports
• Contain one ore more figures to support a certain
  decision situation
• Decision makers can navigate through diffrent
  aggregation levels
• Graphical representation of figures

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Case Study City of Münster

• Located in North Rhine-Westphalia, Germany
• About 270.000 citizens
• Goals of the PICTURE project
• Identification of processes for using document
  managment systems
• Idenfication of reorganisation potentials (e.g.
  ping-pong processes)
• 172 processes modelled in 6 departments
• 38 paper based and later transfered to the Tool
  (2.5h/process)
• 134 directly modelled using the Tool
  (1.5h/process)
• 29 of those modelled by the officals on their
  own
• 20 reports were designed

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Example Ad-hoc Query
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Example Report
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Futher aspects

• Evaluation of the PICTURE-Approach/-Tool
• Increase efficiency of the PICTURE-Approach(e.g.
  by adopting refernce-models)
• Using the PICTURE-Approach to develop a process
  catalogue across differnt public administrations
• Extend the analyses possiblities (e.g. to
  identify monetary impact of reorganisation
  measures)

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Questions
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Contact

• Dr. Lars Algermissen
• algermissen_at_ercis.uni-muenster.de
• 0251-83 3 80 80
• Dipl.-Wirt.-Inf. Daniel Pfeifferpfeiffer_at_ercis.un
  i-muenster.de
• 0251-83 3 80 79
• MScIS Micheal Räckersraekcers_at_ercis.uni-muenster.
  de
• 0251-83 3 80 75

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BACKUP
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Deduction of Process Building Blocks
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Process Definition
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Variant