The Experience of Barcelona Education Consortium's Data-based Records Management System

Data-based records
management:
the experience of Barcelona
Education Consortium(CEB)
Jordi Serra Serra
serra@ub.edu
13º CONGRESSO NACIONAL BAD
Bibliotecarios, arquivistas e documentalistas
25 October 2018
Fundao (Portugal)

THE EXPERIENCE OF BARCELONA
EDUCATION CONSORTIUM

Barcelona Education
Consortium (CEB)
Agency in charge of education in the city
of Barcelona (except University)
60% Generalitat de Catalunya
(Autonomous Government of
Catalonia)
More than
300 public
schools
More than
200 public
funded
private
schools
More than
150 private
schools
40% Ajuntament de Barcelona
(Barcelona City Council)
15
specialized
education
services
10.000
teachers
200
professionals
(CEB headquarters)
Jordi Serra Serra - Data-based records management - 13º CONGRESSO NACIONAL BAD - October 2018 - Fundao (Portugal)

Starting point (june 2016)
180 processes (80% not standardized)
0 digitizised processes
271 technological solutions (62% office tools)
Without any records management system

Work team
Gerència del
Consorci d’Educació
de Barcelona
Direcció d’Atenció a
la Comunitat
Educativa (DACE)
Unitat de Sistemes
d’Informació i
Disseny de
Processos (USIDP)
Àrea de tecnologies
de la informació i
les comunicacions
(TIC)
Several external
providers

Formal goals
To carry out digital
transformation of all
Consortium
processes
And through them
improve the
education of children
and young people in
the city of Barcelona

Real goals
• Achieve the highest control level over the Consortium
activity in order to:
• Know if this activity fullfills the goal to improve the education of
children and young people in the city of Barcelona, and to what
extent it is doing so.
• Know where to apply (surgical) measures to drive the activity of
the Consortium to its main goal.
• In fact, in order to transform the Consortium into a
data-driven organization. And that means having:
• Disagregated and reliable data about CEB activities in real time.
• A detailed picture of Consortium’s processes, data and systems.

Records management system has been conceived at
the Consortium as a piece of a larger gear...
Classification
scheme
Producers list
Access rules
Retention
rules
Records series RM system

Records management system has been conceived at
the Consortium as a piece of a larger gear...
Processes
map
Agents map
Access rules
Retention
rules
Records series
map
Bussines
apps
Publication
rules
Security rules
Systems map
Document
types map
Data map
Office
solutions
Collaboration
tools
Data Bank

SystemsRulesMaps
...that becomes an comprehensive information
management and governance system
Processes
map
Agents map
Access rules
Retention
rules
Records series
map
Bussines
apps
Publication
rules
Security rules
Systems map
Document
types map
Data map
Office
solutions
Collaboration
tools
Data Bank

This means to integrate four kinds of project:

Step 1: Identification and registry
Data mapping
DocTypes mapping
Systems mapping
Records series mapping
Process mapping
Agents mapping

The Consortium has developed a comprehensive
Information Governance System
Data mapping
DocTypes mapping
Systems mapping
Process mapping
Agents mapping

Data mapping
DocTypes mapping
Systems mapping
Process mapping
Agents mapping
A tool developed specifically
for multilevel information
governance (mapping tool)…

Data mapping
DocTypes mapping
Systems mapping
Process mapping
Agents mapping
…with analytical dashboards
for real-time governance of
information assets, data,
processes and systems

Step 2: Analysis and planning
Organizational changes, resources planning and
distribution of tasks and responsibilities
Process improvement, information flow
optimization, and regulatory changes
Standardization and concentration of information
flows and records series
Systems development, security breaches
mitigation, traceability, and interoperability
protocols improvement (systems plan)
Forms standardization, Documents(-like objects)
replacement by data-based evidences
Data quality analysis, data standardization and
information products customization (dashboards)
Data mapping
DocTypes mapping
Systems mapping
Process mapping
Agents mapping

Step 2: Analysis and planning
Organizational changes, sizing of resources and
distribution of competences
Flow optimization, process improvements and
regulatory changes
Normalization, concentration and elimination of
records series
Risks of security breaches, traceability,
functionality and interoperability protocols
improvement (systems plan)
Forms standardization, and replace object-
documents by data-based evidences
Data quality analysis, data normalization and
information needs
Data mapping
DocTypes mapping
Systems mapping
Process mapping
Agents mapping

Step 3: Transformation
Process
optimization and
standardization
Records & info flow
optimization and
standardization
Functional
requirements
definition
Solution
development and
change
management
Data Bank import
processes
development and
DMA creation
Changes into the
organizational
estructure
Data mapping
DocTypes mapping
Systems mapping
Process mapping
Agents mapping

Transformation methodology
1
•Description and analysis of process, records and information flows, and links with information
systems.
2
•Decomposition of records into data. This action builds a process data matrix, that is mapped with
general data model of Consortium Data Bank, setting an specific data model for the process.
3
•Transformation of information systems and applications used by the process (usually office tools)
into a single standardized and safe system.
4
•Transformation of data process inputs and outputs, developing specific electronic forms.
5
•Development of the process to import new system’s data into the Consortium Data Bank, and
scheduling of import actions into the data crawler robot.
6
•Analysis of information needs of process agents, and development of specific dashboards customized
to each kind of user.

FOCUS ON DATA
IN DIGITAL TRANSFORMATION

• “We’ve entered a new era of RIM, with Big
Data at the forefront.”
Kon Leong, 2016

Data only should be used as
evidence for decision-making
when reliable

What do data analysts/scientists demand?
• Reliable data (collected and debugged) for:
• Analysis (Business intelligence)
• Experimentation
• Machine learning / Deep learning
• Good data communication policies.
• Ethics in data use and interpretation.

Data quality factors
• Controlled in its capture
• Protected against modifications
• Traceable in their origin (auditable)
About
reliability
• Not duplicated or redundant
• Standardized (in their values)
• Temporary (current or retrospective)
About
consistency
• Available (preserved)
• Accessible (shared)
• Controlled access
About
functionality

How can we implement
data-based records
management?

Process
Action or
event
Action or
event
Action or
event
Document or data
group
(evidence)
Document or data
group
(evidence)
Document or data
group
(evidence)

Process
Action or
event
Action or
event
Action or
event
Records serie
Document or data
group
(evidence)
Document or data
group
(evidence)
Document or data
group
(evidence)

Process instance
Action or
event
Action or
event
Action or
event
Records aggregation (case file)
Document or data
group
(evidence)
Document or data
group
(evidence)
Document or data
group
(evidence)

Process instance
Student
apply for a
scholarship
Reviewer
assesses the
application
Director
grants the
scholarship
Jaume Pons apply for a
scholarship of 1700 EUR to
take a Master's degree on
10/22/2011
Relating to the scholarship
application of Jaume Pons of
1700 EUR to take a Master's
degree, received on
10/22/2011, me, Sara Vidal,
give my positive advice to
the application on
26/10/2011
Relating to the scholarship
application of Jaume Pons of
1700 EUR to take a Master's
degree, received on
10/22/2011, and positively
advised by Sara Vidal on
October 26, 2011, me,
Mònica Gómez, grant the
amount requested on
10/28/2011

Jaume Pons Jaume Pons Jaume Pons
Apply for 1700 EUR Apply for 1700 EUR Apply for 1700 EUR
To take a Master's degree To take a Master's degree To take a Master's degree
On 22/10/2011 On 22/10/2011 On 22/10/2011
Sara Vidal Sara Vidal
Give a positive advice Give a positive advice
On 26/10/2011 On 26/10/2011
Mònica Gómez
Grant the amount requested
On 28/10/2011
Process instance
Student
apply for a
scholarship
Reviewer
assesses the
application
Director
grants the
scholarship

On 22/10/2011 On 22/10/2011 On 22/10/2011
On 26/10/2011 On 26/10/2011
Mònica Gómez
On 28/10/2011
Process instance
Student
apply for a
scholarship
Reviewer
assesses the
application
Director
grants the
scholarship

The challenge of
interoperability:
the silo culture

On 22/10/2011 On 22/10/2011 On 22/10/2011
On 26/10/2011 On 26/10/2011
Mònica Gómez
On 28/10/2011
Process instance
Student
apply for a
scholarship
Reviewer
assesses the
application
Director
grants the
scholarship
Application (information system)

Process instance
Student
apply for a
scholarship
Reviewer
assesses the
application
Director
grants the
scholarship
Evidencia
(documento en PDF)
<?xml version="1.0"
encoding="UTF-8"?>
<evaluator>Sara
Vidal</evaluator>
<advice>True</advice>
<date>26/10/2011</date>
Application (information system)
Jaume Pons apply for a
scholarship of 1700 EUR to
take a Master's degree on
10/22/2011
Unit resp.: M. Gómez
Decision: Grant
Date: 28/10/2011

File management
Structured data management
Process
Action or
event
Action or
event
Action or
event

It’s not enough to use BI tools
BI system
Data too hard
to collect and
debug
No link with
business
systems

It’s not enough to use an ERM system
BI system
Too difficult for
processing
evidences as
structured data
No link with
business
systems
ERMS

Data management is a key element of
records management
BI system
ERMS
Master data
(transactional)
First step: focus
on each process
(transactional)

records management
BI system
ERMS
Master data
(transactional)
Master data
(reference data)
Second step:
focus on overall
data map
(reference)

records management
BI system
ERMS
Master data
(transactional)
Master data
(reference data)
Needed:
• Standardized technological environments
• Centralized governance body
• Detailed data inventory (map)

records management
BI system
ERMS
Master data
(transactional)
Master data
(reference data)
Or here...
Or here...Or here...
Data can be
standardized
here...

Useful data are reliable (and standardized) data
Created or
received data
(evidence):
within a
document or
information unit
Contextualized
data: within a
file or records
aggregation
(embedded in
the process data
matrix)
Reference data
(unique data):
within a
centralized
registry (MDM)
of potentially
reusable data for
normalization
Data for
analytics
(denormalized):
within a
datamart that
allows uses of
data beyond the
logic of the
process
Record or data
aggregation
Business
application
MDMS BI (Datamart)
Costly option if
data standardization
must be done here
Costly option if
must be done here
Costly option if
must be done here
COST- +

Useful data are reliable (and standardized) data
Created or
received and
standardized
data (verified and
interoperable
evidence): within
a document or
information unit
Contextualized
data: within a
file or records
aggregation
(embedded in
the process data
matrix)
Reference data
(unique data):
within a
centralized
registry (MDM)
of potentially
reusable data for
normalization
Data for
analytics
(denormalized):
within a
datamart that
allows uses of
data beyond the
logic of the
process
Record or data
aggregation
Business
application
MDMS BI (Datamart)
Right option if
can be done here
COST- +

THE CONSORTIUM DATA BANK PROJECT

Gestió de casos de
maltractament
Reconeixement de
NEE
Gestió de
reclamacions
Gestió d’ajuts
menjador
Gestió del
programa EXIT
Fons d’emergència
social
GEDAC - RALC
BDC
...
...
At the beginning of the project, more than 60% of the
information managed by the Consortium was stored in
office tools.
One amount of 168 tools were identified, mostly
spreadsheets, which stored data relevant to the
Consortium.
84% of these tools contained duplicated information,
or data already available in other systems.
The Consortium Data Bank

Gestió de casos de
maltractament
Reconeixement de
NEE
Gestió de
reclamacions
Gestió d’ajuts
menjador
Gestió del
programa EXIT
social
GEDAC - RALC
BDC
...
...
Anna Blanco Anna B.A. Blanco Ana BlacoBlanco, Anna Anna Blanco Blanco, Anna
IDALU 544689
Consortium office tools contained 707 different data fields describing
attributes of students, schools...
A relevant part of these data were potentially standardizable or
already had ID or categorization systems.
Only 54% of the data referring to schools were identified with the ID
of the schools registry.
Only 17% of the data referring to students were linked to the student
ID code (IDALU).

Gestió de casos de
maltractament
Reconeixement de
NEE
Gestió de
reclamacions
Gestió d’ajuts
menjador
Gestió del
programa EXIT
social
GEDAC - RALC
BDC
...
...
IDALU 544689
The goal of the Consortium Data Bank has been to
offer unique and reliable data...
...in a safe environment with user access control...
...linked to the rest of the Consortium data...
...and as a product ready for immediate user’s use.

Gestió de casos de
maltractament
Reconeixement de
NEE
Gestió de
reclamacions
Gestió d’ajuts
menjador
Gestió del
programa EXIT
social
GEDAC - RALC
BDC
...
...
IDALU 544689
Ana Blanco
IDALU 544689
Ana Blanco
IDALU 544689
Ana Blanco
IDALU 544689
Ana Blanco
IDALU 544689
Ana Blanco
IDALU 544689
Ana Blanco
IDALU 544689
Original (reference and transactional) data are imported into
the Data Bank on a regular basis, using a data crawler robot,
and in this process data are normalized to ensure the
uniqueness of all data.

Gestió de casos de
maltractament
Reconeixement de
NEE
Gestió de
reclamacions
Gestió d’ajuts
menjador
Gestió del
programa EXIT
social
GEDAC - RALC
BDC
...
...
IDALU 544689
Ana Blanco
IDALU 544689
Ana Blanco
IDALU 544689
Ana Blanco
IDALU 544689
Ana Blanco
IDALU 544689
Ana Blanco
IDALU 544689
Ana Blanco
IDALU 544689
Ana Blanco
IDALU 544689
Then data are processed to allow
360° views focused on every
Consortium activity significant
item (student, school, etc.)

Gestió de casos de
maltractament
Reconeixement de
NEE
Gestió de
reclamacions
Gestió d’ajuts
menjador
Gestió del
programa EXIT
social
GEDAC - RALC
BDC
...
...
IDALU 544689
Ana Blanco
IDALU 544689
Ana Blanco
IDALU 544689
Ana Blanco
IDALU 544689
Ana Blanco
IDALU 544689
Ana Blanco
IDALU 544689
Ana Blanco
IDALU 544689
Ana Blanco
IDALU 544689
Progressive transformation of office and personal data
sources to corporate standard applications ensures reliability
of data and increases the frequency of data imports.
Ana Blanco
IDALU 544689
Ana Blanco
IDALU 544689
Ana Blanco
IDALU 544689
Ana Blanco
IDALU 544689

Gestió de casos de
maltractament
Reconeixement de
NEE
Gestió de
reclamacions
Gestió d’ajuts
menjador
Gestió del
programa EXIT
social
GEDAC - RALC
BDC
...
...
IDALU 544689
Ana Blanco
IDALU 544689
Ana Blanco
IDALU 544689
Ana Blanco
IDALU 544689
Ana Blanco
IDALU 544689
Ana Blanco
IDALU 544689
Ana Blanco
IDALU 544689
This allows fast development of customized data
visualizations satisfying the needs of every Data Bank
customer (units, staff, etc.)
Ana Blanco
IDALU 544689

About Records Management “System”:
• Records (and information) management is a service,
not just a system.
• Records (and information) management should end
always in an efficient information service.
• "We are not an information service... We are the
information".
• Every information product will be better if it is
complete (finished) and tailored to the user.

About Data-based management:
• Providing a collection of documents-like-objects as information
product is not the best answer to an information need, and
significantly limits the quality of the service. Going beyond this
limit means basing services design on data.
• Focus on data is a must if you want to offer customized information
products.
• This involves to fight a second battle against some user’s feeling to
consider information (often stored on spreadsheets) as a personal
asset instead of a corporate asset. Break down information silos,
even informal or personal silos, is the first step to build a successful
corporate information service.

About system’s sustainability:
• Efficiency in the development and implementation of a records
and information management system is the key factor to offer
successful services. Efficiency should therefore guide the
construction, implementation and maintenance of the system. That
means:
• Invest a rational effort designing and developing the system
• Justify this investment as soon as possible with tangible results
• Offer better and more powerful information products
• All solutions had an expiration date, and must be reevaluated
periodically.
• Change cannot be imposed. Change managemente needs time,
patience, perseverance and burning one stage after another.

About the information governance system:
• An Information Governance System is an observatory
for monitoring, analysis, planning and development of
new solutions.
• The System must provide a global vision to ensure:
• Standardization and quality of data on its creation time
• Reuse and relationships between data on access time
• But, at the same time, System should be able to be
implemented in different technological platforms,
taking care of specific needs of each process and its
records and information flow.

About the results:
• Our goal isn't to build systems, but to improve daily operation of our
organization.
• Records and information management systems should produce results in
key processes. If they don't this, they are not useful for the organization.
• To achieve this goal, work must not be done analyzing records or
documents, but analyzing the decisions taken in the course of each
process and the conditions in which they are taken (information flow).
• In a data-driven world, records management often continues sacralizing
the document. In fact, decision-making needs only reliable data, doesn’t
matter its documentary form. If data are authenticated in its origin as
structured data (for example using blockchain technology), document-like-
object becomes an almost unnecessary formality.

About the impact in decision-making:
• Availability of on-time reliable data opens new perspectives in regard to:
• Public policies design (Evidence-Based Policymaking).
• Promotion of public services proactive actions.
• Predictive analytics and artificial intelligence applied to public services.
• Availability of real time data becomes a maturity test for organizations
and their decision-makers. Specially in public sector, where it can often
promote an overall rethinking of policies, services, strategic and
operational work plans.
• Application of artificial intelligence involves an even greater issue, given
its impact on workloads and professional profiles.
• Concentration of data into centralized, automated and open services
harshly disrupts tacit power structures in organizations (often based on
information monopolization in a few hands).

Muito obrigado
Jordi Serra Serra
serra@ub.edu
13º CONGRESSO NACIONAL BAD
Bibliotecarios, arquivistas e documentalistas
25 de Octubre de 2018
Fundao (Portugal)

The Experience of Barcelona Education Consortium's Data-based Records Management System

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