ISO 8000-64:2022

Data quality - Part 64: Data quality management: Organizational process maturity assessment: Application of the Test Process Improvement method

This document specifies how to apply the Test Process Improvement method to the assessment of organizational process maturity. This document refines the language in the method, which has an original purpose of more than just data quality management. This document supports improving data quality management when an organization uses the process reference model in ISO 8000‑61 as the foundation for specifying the measurement goals for the process measurement necessary when performing maturity assessment. The following are within scope of this document: - the relationship between the Test Process Improvement method[11][12] and the procedure for assessing process maturity of data quality management as specified by ISO 8000‑61; - the role of process measurement in accordance with ISO 8000‑63 when performing assessment of process maturity; - the outputs from the procedure. The following are outside the scope of this document: - the purpose, outcomes and activities of processes for data quality management; - specific content for the scope of individual quality management areas, the maturity levels and the maturity level targets; - specific content for each inspection order including the frequency of inspection points; - instructions on how to develop a process improvement strategy in response to the outputs of the procedure. This document can be used in conjunction with or independently of quality management systems standards.

Qualité des données — Partie 64: Gestion de la qualité des données : Évaluation de la maturité des processus organisationnels : Application de la méthode d'amélioration des processus de test (TPI, Test Process Improvement)

General Information

• Status: Published
• Publication Date: 16-May-2022
• ICS: 25.040.40 - Industrial process measurement and control
• Technical Committee: ISO/TC 184/SC 4 - Industrial data
• Drafting Committee: ISO/TC 184/SC 4/WG 13 - Industrial Data Quality
• Current Stage: 6060 - International Standard published
• Start Date: 17-May-2022
• Due Date: 04-Nov-2021
• Completion Date: 17-May-2022

Overview

ISO 8000-64:2022 - Data quality - Part 64 - specifies how to apply the Test Process Improvement (TPI) method to assess organizational process maturity with a focus on improving data quality management. Published in 2022, this part of the ISO 8000 series refines TPI language for use in data quality contexts and ties maturity assessment to the process reference model and measurement requirements defined elsewhere in ISO 8000.

Key topics and technical requirements

• Application of the TPI method: Adapts the Test Process Improvement approach so it is suitable for assessing data quality management processes.
• Alignment with ISO 8000-61: Uses the ISO 8000-61 process reference model as the foundation for specifying measurement goals that support maturity assessment.
• Process measurement role (ISO 8000-63): Requires process measurement and an inspection plan in accordance with ISO 8000-63 to collect the evidence needed for maturity evaluation.
• Procedure steps (procedure 0–7): Defines a structured assessment procedure including:
  • Prepare core assessment elements (step 0)
  • Define quality management areas (step 1)
  • Define maturity levels (step 2) and maturity level targets (step 3)
  • Define inspection plan (step 4) and inspection orders (step 5)
  • Generate quality management area values (step 6)
  • Identify maturity level improvement requirements (step 7)
• Outputs: Specifies the expected outputs from the maturity assessment procedure (e.g., quality area values and identified improvement requirements).
• In-scope vs out-of-scope: Clarifies that the standard addresses assessment procedure and measurement relationships, but does not define process outcomes, specific maturity level content, inspection frequencies, or how to develop a process improvement strategy.

Practical applications - who should use it

• Data governance leaders and data quality managers seeking a repeatable maturity assessment approach.
• Process improvement teams and quality assurance professionals adopting TPI for data domains.
• CIOs, enterprise architects, and compliance officers who need evidence-based assessments of data-related processes.
• External auditors and consultants conducting organizational maturity evaluations tied to data quality.
• Organizations implementing or aligning with the ISO 8000 series as part of digital transformation or data governance programs.

Benefits and outcomes

• A structured, measurable way to assess and track data quality process maturity.
• Clear linkage between measurement goals, process reference models and maturity outputs.
• Flexibility to define quality management areas that match organizational priorities.
• Can be used independently of formal quality management system standards.

Related standards

• ISO 8000-2 - Data quality: Vocabulary
• ISO 8000-61 - Data quality management: Process reference model
• ISO 8000-63 - Data quality management: Process measurement
• Reference: ISO/IEC 33020 (different approach to fixed process attributes)

Keywords: ISO 8000-64, data quality management, process maturity assessment, Test Process Improvement, TPI, process measurement, data governance, maturity model.

Standards Content (Sample)

INTERNATIONAL ISO
STANDARD 8000-64
First edition
2022-05
Data quality —
Part 64:
Data quality management:
Organizational process maturity
assessment: Application of the Test
Process Improvement method
Qualité des données —
Partie 64: Gestion de la qualité des données : Évaluation de la
maturité des processus organisationnels : Application de la méthode
d'amélioration des processus de test (TPI, Test Process Improvement)
Reference number
© ISO 2022
All rights reserved. Unless otherwise specified, or required in the context of its implementation, no part of this publication may
be reproduced or utilized otherwise in any form or by any means, electronic or mechanical, including photocopying, or posting on
the internet or an intranet, without prior written permission. Permission can be requested from either ISO at the address below
or ISO’s member body in the country of the requester.
ISO copyright office
CP 401 • Ch. de Blandonnet 8
CH-1214 Vernier, Geneva
Phone: [phone]
Email: [e-mail]
Website: www.iso.org
Published in Switzerland
ii
Contents Page
Foreword .iv
Introduction .v
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 2
4 Process maturity assessment . 2
5 Procedure for maturity assessment .3
5.1 Foundations and steps of the procedure . 3
5.2 Prepare core assessment elements (procedure step 0) . 4
5.3 Define quality management areas (procedure step 1) . 4
5.4 Define maturity levels (procedure step 2) . 5
5.5 Define maturity level targets (procedure step 3) . 5
5.6 Define inspection plan (procedure step 4) . 5
5.7 Prepare and apply inspection order (procedure step 5) . 6
5.8 Generate quality management area values (procedure step 6) . 7
5.9 Identify the maturity level improvement requirement (procedure step 7) . 8
5.10 Applying the procedure to data quality management processes . 8
Annex A (informative) Document identification .10
Annex B (informative) Example process maturity assessment .11
Bibliography .15
iii
Foreword
ISO (the International Organization for Standardization) is a worldwide federation of national standards
bodies (ISO member bodies). The work of preparing International Standards is normally carried out
through ISO technical committees. Each member body interested in a subject for which a technical
committee has been established has the right to be represented on that committee. International
organizations, governmental and non-governmental, in liaison with ISO, also take part in the work.
ISO collaborates closely with the International Electrotechnical Commission (IEC) on all matters of
electrotechnical standardization.
The procedures used to develop this document and those intended for its further maintenance are
described in the ISO/IEC Directives, Part 1. In particular, the different approval criteria needed for the
different types of ISO documents should be noted. This document was drafted in accordance with the
editorial rules of the ISO/IEC Directives, Part 2 (see www.iso.org/directives).
Attention is drawn to the possibility that some of the elements of this document may be the subject of
patent rights. ISO shall not be held responsible for identifying any or all such patent rights. Details of
any patent rights identified during the development of the document will be in the Introduction and/or
on the ISO list of patent declarations received (see www.iso.org/patents).
Any trade name used in this document is information given for the convenience of users and does not
constitute an endorsement.
For an explanation of the voluntary nature of standards, the meaning of ISO specific terms and
expressions related to conformity assessment, as well as information about ISO’s adherence to
the World Trade Organization (WTO) principles in the Technical Barriers to Trade (TBT), see
www.iso.org/iso/foreword.html.
This document was prepared by Technical Committee ISO/TC 184, Automation systems and integration,
Subcommittee SC 4, Industrial data.
A list of all parts in the ISO 8000 series can be found on the ISO website.
Any feedback or questions on this document should be directed to the user’s national standards body. A
complete listing of these bodies can be found at www.iso.org/members.html.
iv
Introduction
Digital data deliver value by enhancing all aspects of organizational performance including:
— operational effectiveness and efficiency;
— safety;
— reputation with customers and the wider public;
— compliance with statutory regulations;
— innovation;
— consumer costs, revenues and stock prices.
In addition, many organizations are now addressing these considerations with reference to the United
1)
Nations Sustainable Development Goals .
The influence on performance originates from data being the formalized representation of
2)
information . This information enables organizations to make reliable decisions. This decision making
can be performed by human beings directly and also by automated data processing including artificial
intelligence systems.
Through widespread adoption of digital computing and associated communication technologies,
organizations become dependent on digital data. This dependency amplifies the negative consequences
of lack of quality in these data. These consequences are the decrease of organizational performance.
The biggest impact of digital data comes from two key factors:
— the data having a structure that reflects the nature of the subject matter;
EXAMPLE 1 A research scientist writes a report using a software application for word processing. This report
includes a table that uses a clear, logical layout to show results from an experiment. These results indicate how
material properties vary with temperature. The report is read by a designer, who uses the results to create a
product that works in a range of different operating temperatures.
— the data being computer processable (machine readable) rather than just being for a person to read
and understand.
EXAMPLE 2 A research scientist uses a database system to store the results of experiments on a material.
This system controls the format of different values in the data set. The system generates an output file of digital
data. This file is processed by a software application for engineering analysis. The application determines the
optimum geometry when using the material to make a product.
ISO 9000 explains that quality is not an abstract concept of absolute perfection. Quality is actually
the conformance of characteristics to requirements. This actuality means that any item of data can
be of high quality for one purpose but not for a different purpose. The quality is different because the
requirements are different between the two purposes.
EXAMPLE 3 Time data are processed by calendar applications and also by control systems for propulsion
units on spacecraft. These data include start times for meetings in a calendar application and activation times in
a control system. These start times require less precision than the activation times.
The nature of digital data is fundamental to establishing requirements that are relevant to the specific
decisions that are made by each organization.
EXAMPLE 4 ISO 8000-1 identifies that data have syntactic (format), semantic (meaning) and pragmatic
(usefulness) characteristics.
1) https://sdgs.un.org/goals
2) ISO 8000-2 defines information as “knowledge concerning objects, such as facts, events, things, processes, or
ideas, including concepts, that within a certain context has a particular meaning”.
v
To support the delivery of high-quality data, the ISO 8000 series addresses:
— data governance, data quality management and maturity assessment;
EXAMPLE 5 ISO 8000-61 specifies a process reference model for data quality management.
— creating and applying requirements for data and information;
EXAMPLE 6 ISO 8000-110 specifies how to exchange characteristic data that are master data.
— monitoring and measuring information and data quality;
EXAMPLE 7 ISO 8000-8 specifies approaches to measuring information and data quality.
— improving data and, consequently, information quality;
EXAMPLE 8 ISO/TS 8000-81 specifies an approach to data profiling, which identifies opportunities to improve
data quality.
— issues that are specific to the type of content in a data set.
EXAMPLE 9 ISO/TS 8000-311 specifies how to address quality considerations for product shape data.
Data quality management covers all aspects of data processing, including creating, collecting, storing,
maintaining, transferring, exploiting and presenting data to deliver information.
Effective data quality management is systemic and systematic, requiring an understanding of the
root causes of data quality issues. This understanding is the basis for not just correcting existing
nonconformities but for also implementing solutions that prevent future reoccurrence of those
nonconformities.
EXAMPLE 10 If a data set includes dates in multiple formats including “yyyy-mm-dd”, “mm-dd-yy” and
“dd-mm-yy”, then data cleansing can correct the consistency of the values. Such cleansing requires additional
information, however, to resolve ambiguous entries (such as, “04-05-20”). The cleansing also cannot address any
process issues and people issues, including training, that have caused the inconsistency.
As a contribution to this overall capability of the ISO 8000 series, this document specifies a procedure
by which any organization can assess process maturity according to the specific priorities of the
organization. This procedure provides a capability to assess and improve data quality management
[11][12]3)
processes. The procedure makes use of the Test Process Improvement method .
Organizations can use this document on its own or in conjunction with other parts of the ISO 8000
series.
This document supports activities that affect:
— one or more information systems;
— data flows within the organization and with external organizations;
— any phase of the data life cycle.
By implementing parts of the ISO 8000 series to improve organizational performance, an organization
achieves the following benefits:
— objective validation of the foundations for digital transformation of the organization;
— a sustainable basis for data in digital form becoming a fundamental asset class the organization
relies on to deliver value;
— securing evidence-based trust from other parties (including supply chain partners and regulators)
about the repeatability and reliability of data and information processing in the organization;
3) Numbers in square brackets refer to entries in the Bibliography.
vi
— portability of data with resulting protection against loss of intellectual property and reusability
across the organization and applications;
— effective and efficient interoperability between all parties in a supply chain to achieve traceability
of data back to original sources;
— readiness to acquire or supply services where the other party expects to work with common
understanding of explicit data requirements.
ISO 8000-1 provides a detailed explanation of the structure and scope of the whole ISO 8000 series.
4)
ISO 8000-2 specifies the single, common vocabulary for the ISO 8000 series. This vocabulary is ideal
reading material by which to understand the overall subject matter of data quality. ISO 8000-2 presents
the vocabulary structured by a series of topic areas (for example, terms relating to quality and terms
relating to data and information).
Annex A of this document contains an identifier that conforms to ISO/IEC 8824-1. The identifier
unambiguously identifies this document in an open information system.
4) The content is available on the ISO Online Browsing Platform. https://www.iso.org/obp
vii
INTERNATIONAL STANDARD ISO 8000-64:2022(E)
Data quality —
Part 64:
Data quality management: Organizational process
maturity assessment: Application of the Test Process
Improvement method
1 Scope
This document specifies how to apply the Test Process Improvement method to the assessment of
organizational process maturity. This document refines the language in the method, which has an
original purpose of more than just data quality management. This document supports improving
data quality management when an organization uses the process reference model in ISO 8000-61 as
the foundation for specifying the measurement goals for the process measurement necessary when
performing maturity assessment.
The following are within scope of this document:
[11][12]
— the relationship between the Test Process Improvement method and the procedure for
assessing process maturity of data quality management as specified by ISO 8000-61;
— the role of process measurement in accordance with ISO 8000-63 when performing assessment of
process maturity;
— the outputs from the procedure.
The following are outside the scope of this document:
— the purpose, outcomes and activities of processes for data quality management;
— specific content for the scope of individual quality management areas, the maturity levels and the
maturity level targets;
— specific content for each inspection order including the frequency of inspection points;
— instructions on how to develop a process improvement strategy in response to the outputs of the
procedure.
This document can be used in conjunction with or independently of quality management systems
standards.
2 Normative references
The following documents are referred to in the text in such a way that some or all of their content
constitutes requirements of this document. For dated references, only the edition cited applies. For
undated references, the latest edition of the referenced document (including any amendments) applies.
ISO 8000-2, Data quality — Part 2: Vocabulary
ISO 8000-61, Data quality — Part 61: Data quality management: Process reference model
ISO 8000-63, Data quality — Part 63: Data quality management: Process measurement
3 Terms and definitions
For the purposes of this document, the terms and definitions given in ISO 8000-2 apply.
ISO and IEC maintain terminology databases for use in standardization at the following addresses:
— ISO Online browsing platform: available at https:// www .iso .org/ obp
— IEC Electropedia: available at https:// www .electropedia .org/
4 Process maturity assessment
This document specifies a procedure for assessing process maturity. This procedure builds on the
requirements for process measurement specified by ISO 8000-63. The procedure provides a flexible
approach to meet the requirements of an organization using the procedure. This flexibility is from the
organization being able to define quality management areas that depend on the factors identified by the
organization as being most relevant when seeking to improve process maturity.
EXAMPLE 1 ISO/IEC 33020 differs from this document by specifying a fixed set of process attributes for use in
maturity assessment.
EXAMPLE 2 An organization chooses to make each quality management area correspond to the responsibilities
of a single role within the organization.
Each quality management area covers one or more measurement goals that are the basis for process
measurement supporting the maturity assessment. The assessment enables an organization to drive
progressive improvement of process maturity but does not establish a general benchmark for use by
the organization to compare itself with other organizations.
EXAMPLE 3 Two organizations define different quality management areas and, therefore, are unable directly
to compare the results from assessing process maturity.
The procedure highlights those quality management areas that have yet to reach the required target
for overall process maturity to reach the next level. These quality management areas become the focus
for improvement.
The initial steps of the procedure set up the organization to be able to perform maturity assessment.
This set up shall include, in accordance with ISO 8000-63, creating an inspection plan for the process
measurement. The organization can then proceed to use the rest of the procedure to perform
assessments at appropriate frequencies to track the evolution of maturity.
EXAMPLE 4 An organization creates an inspection plan and then decides to assess process maturity every six
months.
To establish a basis for improving data quality management (see Figure 1), the process maturity
assessment shall:
— assess implementations of processes specified by ISO 8000-61;
— execute the procedure as specified by Clause 5.
Key
CIV1, CIV2 etc. converted indicator values
G1, G2 etc. goals
MV2, MV3 etc. measured values
QMA1, QMA2 etc. quality management areas
QMAT1, QMAT2 etc. quality management area targets
QMAV1, QMAV2 etc. quality management area values
Figure 1 — Process measurement and process maturity assessment
5 Procedure for maturity assessment
5.1 Foundations and steps of the procedure
The procedure in this document takes account of three elements of the Test Process Improvement
[11][12]
me
...