SIST ISO 10017:2021
Quality management - Guidance on statistical techniques for ISO 9001:2015
Quality management - Guidance on statistical techniques for ISO 9001:2015
This document gives guidelines for the selection of appropriate statistical techniques that can be useful
to an organization, irrespective of size or complexity, in developing, implementing, maintaining and
improving a quality management system in conformity with ISO 9001:2015.
This document does not provide guidance on how to use the statistical techniques.
Management de la qualité — Recommandations relatives aux techniques statistiques pour l’ISO 9001:2015
Vodenje kakovosti - Napotki za statistične metode v zvezi z ISO 9001:2015
General Information
Relations
Standards Content (Sample)
SLOVENSKI STANDARD
SIST ISO 10017:2021
01-september-2021
Nadomešča:
SIST ISO/TR 10017:2003
Vodenje kakovosti - Napotki za statistične metode v zvezi z ISO 9001:2015
Quality management - Guidance on statistical techniques for ISO 9001:2015
Management de la qualité — Recommandations relatives aux techniques statistiques
pour l’ISO 9001:2015
Ta slovenski standard je istoveten z: ISO 10017:2021
ICS:
03.120.10 Vodenje in zagotavljanje Quality management and
kakovosti quality assurance
03.120.30 Uporaba statističnih metod Application of statistical
methods
SIST ISO 10017:2021 en
2003-01.Slovenski inštitut za standardizacijo. Razmnoževanje celote ali delov tega standarda ni dovoljeno.
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SIST ISO 10017:2021
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SIST ISO 10017:2021
INTERNATIONAL ISO
STANDARD 10017
First edition
2021-07
Quality management — Guidance
on statistical techniques for
ISO 9001:2015
Management de la qualité — Recommandations relatives
aux techniques statistiques pour l’ISO 9001:2015
Reference number
ISO 10017:2021(E)
©
ISO 2021
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SIST ISO 10017:2021
ISO 10017:2021(E)
COPYRIGHT PROTECTED DOCUMENT
© ISO 2021
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: +41 22 749 01 11
Email: copyright@iso.org
Website: www.iso.org
Published in Switzerland
ii © ISO 2021 – All rights reserved
---------------------- Page: 4 ----------------------
SIST ISO 10017:2021
ISO 10017:2021(E)
Contents Page
Foreword .v
Introduction .vi
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Statistical techniques in the implementation of ISO 9001 . 1
5 Quantitative data and associated statistical techniques in ISO 9001 .2
6 Applicability of selected techniques . 9
7 Description of statistical techniques . 9
7.1 Descriptive statistics . 9
7.1.1 General description . 9
7.1.2 Benefits .11
7.1.3 Limitations and cautions .11
7.1.4 Examples of applications .12
7.2 Design of experiments .12
7.2.1 General description .12
7.2.2 Benefits .12
7.2.3 Limitations and cautions .13
7.2.4 Examples of applications .13
7.3 Hypothesis testing .13
7.3.1 General description .13
7.3.2 Benefits .14
7.3.3 Limitations and cautions .14
7.3.4 Examples of applications .14
7.4 Measurement system analysis .14
7.4.1 General description .14
7.4.2 Benefits .15
7.4.3 Limitations and cautions .15
7.4.4 Examples of applications .15
7.5 Process capability analysis .15
7.5.1 General description .15
7.5.2 Benefits .16
7.5.3 Limitations and cautions .16
7.5.4 Examples of applications .17
7.6 Regression analysis .17
7.6.1 General description .17
7.6.2 Benefits .18
7.6.3 Limitations and cautions .18
7.6.4 Examples of applications .19
7.7 Reliability analysis .19
7.7.1 General description .19
7.7.2 Benefits .20
7.7.3 Limitations and cautions .20
7.7.4 Examples of applications .20
7.8 Sampling .21
7.8.1 General description .21
7.8.2 Benefits .21
7.8.3 Limitations and cautions .21
7.8.4 Examples of applications .22
7.9 Simulation .22
7.9.1 General description .22
7.9.2 Benefits .22
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SIST ISO 10017:2021
ISO 10017:2021(E)
7.9.3 Limitations and cautions .23
7.9.4 Examples of applications .23
7.10 Statistical process control .23
7.10.1 General description .23
7.10.2 Benefits .24
7.10.3 Limitations and cautions .25
7.10.4 Examples of applications .25
7.11 Statistical tolerance .25
7.11.1 General description .25
7.11.2 Benefits .26
7.11.3 Limitations and cautions .26
7.11.4 Examples of applications .26
7.12 Time series analysis .26
7.12.1 General description .26
7.12.2 Benefits .27
7.12.3 Limitations and cautions .27
7.12.4 Examples of applications .28
Bibliography .29
iv © ISO 2021 – All rights reserved
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SIST ISO 10017:2021
ISO 10017:2021(E)
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 176, Quality management and quality
assurance, Subcommittee SC 3, Supporting technologies.
This first edition of ISO 10017 cancels and replaces ISO/TR 10017:2003, which has been technically
revised. The main changes compared with ISO/TR 10017:2003 are as follows:
— it has been revised as a full guidance document and aligned with ISO 9001:2015.
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.
© ISO 2021 – All rights reserved v
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SIST ISO 10017:2021
ISO 10017:2021(E)
Introduction
Variability is inherent in the behaviour and outcome of practically all processes and activities, even
under conditions of apparent stability. Such variability can be observed, over the total life cycle, in the
quantifiable characteristics of processes and in the resulting products and services.
Statistical techniques can help to measure, describe, analyse, interpret and model variability (whether
dealing with a relatively limited amount of data or with large data sets). Statistical analysis of data can
provide a better understanding of the nature, extent and causes of variability. It can help to solve and
even prevent problems and mitigate risks that can stem from such variability.
The analysis of data using statistical techniques can assist in decision-making and thereby help to
improve the performance of processes and the resulting outputs. Statistical techniques are applicable
to data in all sectors, with potentially beneficial outcomes.
The criteria for determining the need for statistical techniques, and the appropriateness of the
technique(s) selected, remain the prerogative of the organization.
The purpose of this document is to assist an organization in identifying statistical techniques against
the elements of a quality management system as defined by ISO 9001:2015. The application of such
techniques can yield considerable benefits in quality, productivity and cost.
This document can be also used to support other management systems and supporting standards, e.g.
an environmental management system, a health and safety management system.
vi © ISO 2021 – All rights reserved
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SIST ISO 10017:2021
INTERNATIONAL STANDARD ISO 10017:2021(E)
Quality management — Guidance on statistical techniques
for ISO 9001:2015
1 Scope
This document gives guidelines for the selection of appropriate statistical techniques that can be useful
to an organization, irrespective of size or complexity, in developing, implementing, maintaining and
improving a quality management system in conformity with ISO 9001:2015.
This document does not provide guidance on how to use the statistical techniques.
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 3534-1, Statistics — Vocabulary and symbols — Part 1: General statistical terms and terms used in
probability
ISO 3534-2, Statistics — Vocabulary and symbols — Part 2: Applied statistics
ISO 3534-3, Statistics — Vocabulary and symbols — Part 3: Design of experiments
ISO 3534-4, Statistics — Vocabulary and symbols — Part 4: Survey sampling
ISO 9000:2015, Quality management systems — Fundamentals and vocabulary
3 Terms and definitions
For the purposes of this document, the terms and definitions given in ISO 3534-1, ISO 3534-2,
ISO 3534-3, ISO 3534-4, ISO 9000:2015 and the following apply.
ISO and IEC maintain terminological databases for use in standardization at the following addresses:
— ISO Online browsing platform: available at https:// www .iso .org/ obp
— IEC Electropedia: available at http:// www .electropedia .org/
3.1
statistical technique
statistical method
methodology for the analysis of quantitative data associated with variation in products, processes,
services and phenomena under study to provide information on the object of the study
Note 1 to entry: Statistical techniques are equally applicable to qualitative (non-numeric) data if such data can be
converted to quantitative (numeric) data.
4 Statistical techniques in the implementation of ISO 9001
Statistical techniques can help to evaluate, control and improve processes and their resulting outputs,
and help to assess and improve the effectiveness of a quality management system.
© ISO 2021 – All rights reserved 1
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SIST ISO 10017:2021
ISO 10017:2021(E)
Statistical techniques, or families of techniques, that are widely used, and which find useful application
in the implementation of ISO 9001 include:
— descriptive statistics (see 7.1);
— design of experiments (DOE) (see 7.2);
— hypothesis testing (see 7.3);
— measurement system analysis (MSA) (see 7.4);
— process capability analysis (see 7.5);
— regression analysis (see 7.6);
— reliability analysis (see 7.7);
— sampling (see 7.8);
— simulation (see 7.9);
— statistical process control (SPC) (see 7.10);
— statistical tolerance (see 7.11);
— time series analysis (see 7.12).
Many of these techniques are used in conjunction with other techniques or as sub-sets of other
statistical techniques.
The list of statistical techniques cited in this document is neither complete nor exhaustive and does not
preclude the use of any other techniques (statistical or otherwise) that are deemed to be beneficial to
the organization. Furthermore, this document does not attempt to specify which statistical technique(s)
should be used and it does not attempt to advise on how the technique(s) should be implemented.
5 Quantitative data and associated statistical techniques in ISO 9001
Quantitative data that can reasonably be encountered in activities associated with the clauses and
subclauses of ISO 9001:2015 are noted in Table 1. Listed against the quantitative data identified are
statistical techniques that can be of potential benefit to the organization when applied to such data.
No statistical techniques have been identified where quantitative data cannot be readily associated
with a clause or sub-clause of ISO 9001.
The statistical techniques cited in this document are limited to those that are well known. A brief
description of each of these statistical techniques is given in Clause 7.
The organization can assess the relevance and value of each statistical technique listed in Table 1 and
determine whether it is useful in the context of that clause.
Table 1 — Quantitative data and possible statistical technique(s)
Clause/subclause of Quantitative data involved Statistical technique(s)
ISO 9001:2015
1. Scope Not applicable —
2. Normative references Not applicable —
3. Terms and definitions Not applicable —
4. Context of the organization
2 © ISO 2021 – All rights reserved
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SIST ISO 10017:2021
ISO 10017:2021(E)
Table 1 (continued)
Clause/subclause of Quantitative data involved Statistical technique(s)
ISO 9001:2015
4.1 Understanding the organ- Data regarding internal and external Descriptive statistics
ization and its context issues, for example:
Statistical process control
— financial
Sampling
— employee surveys
Time series analysis
— market research
— sales
— product and service performance
— competition/benchmarking
— customer surveys
4.2 Understanding the needs Subjective and objective data regarding Descriptive statistics
and expectations of interest- the expectations of interested parties
Sampling
ed parties (e.g. market research, customer sur-
veys, employee surveys) Time series analysis
4.3 Determining the scope None identified —
of the quality management
system
4.4 Quality management system and its processes
4.4.1 None identified —
4.4.2 None identified —
5. Leadership
5.1 Leadership and commitment
5.1.1 General None identified —
5.1.2 Customer focus None identified —
5.2 Policy
5.2.1 Establishing the quality None identified —
policy
5.2.2 Communicating the Data to determine the extent to which Descriptive statistics
quality policy the policy is understood
Sampling
5.3 Organizational roles, re- None identified —
sponsibilities and authorities
6 Planning
6.1 Actions to address risks and opportunities
6.1.1 Business data to assess risks Descriptive statistics
6.1.2 Business data to assess the effective- Descriptive statistics
ness of actions taken
6.2 Quality objectives and planning to achieve them
6.2.1 Historical performance data to assist —
establishing quality goals
6.2.2 Historical performance data to assist —
establishing quality goals
6.3 Planning of changes Historical performance data to assist —
establishing quality goals
7 Support
7.1 Resources
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SIST ISO 10017:2021
ISO 10017:2021(E)
Table 1 (continued)
Clause/subclause of Quantitative data involved Statistical technique(s)
ISO 9001:2015
7.1.1 General Summary data on capability Descriptive statistics
7.1.2 People None identified —
7.1.3 Infrastructure Quantitative data related to the per- Descriptive statistics
formance and reliability of equipment
Process capability analysis
(hardware and software) and trans-
portation Reliability analysis
7.1.4 Environment for the Data on the environment, for example: Descriptive statistics
operation of processes
— contamination levels
Measurement system analysis
Process capability analysis
— antistatic controls
Sampling
— temperatures (e.g. bacteria
control) Statistical process control
Time series analysis
— morale (e.g. absenteeism)
7.1.5 Monitoring and measuring resources
7.1.5.1 General Data relating to measurement capabil- Descriptive statistics
ity
Measurement system analysis
Statistical tolerance
7.1.5.2 Measurement tracea- Data relating to the stability of meas- Descriptive statistics
bility urement systems
Time series analysis
7.1.6 Organizational knowl- None identified —
edge
7.2 Competence Quantitative data on training and the Descriptive statistics
effectiveness of training
Hypothesis testing
7.3 Awareness Data regarding the level of awareness Descriptive statistics
of quality policy and objectives
Sampling
7.4 Communication None identified —
7.5 Documented information
7.5.1 General None identified —
7.5.2 Creating and updating None identified —
7.5.3 Control of documented information
7.5.3.1 None identified —
7.5.3.2 None identified —
8 Operation
8.1 Operational planning and No specific data identified —
control
8.2 Requirements for products and services
8.2.1 Customer communica- None identified —
tion
4 © ISO 2021 – All rights reserved
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SIST ISO 10017:2021
ISO 10017:2021(E)
Table 1 (continued)
Clause/subclause of Quantitative data involved Statistical technique(s)
ISO 9001:2015
8.2.2 Determining the re- Data to demonstrate capability and Descriptive statistics
quirements for products and organizational performance
Hypothesis testing
services
Measurement system analysis
Process capability analysis
Regression analysis
Reliability analysis
Sampling
Statistical process control
8.2.3 Review of the requirements for products and services
8.2.3.1 Data to demonstrate capability and Descriptive statistics
organizational performance
Hypothesis testing
Measurement system analysis
Process capability analysis
Reliability analysis
Statistical process control
8.2.3.2 None identified —
8.2.4 Changes to require- None identified —
ments for products and
services
8.3 Design and development of products and services
8.3.1 General None identified —
8.3.2 Design and develop- None identified —
ment planning
8.3.3 Design and develop- None identified —
ment inputs
8.3.4 Design and develop- Verification and validation of design Descriptive statistics
ment controls data
Design of experiments
Hypothesis testing
Regression analysis
Sampling
Simulation
Statistical tolerance
8.3.5 Design and develop- Verification of design output data Descriptive statistics
ment outputs
Hypothesis testing
Process capability analysis
Simulation
8.3.6 Design and develop- Data related to-verification of the im- Descriptive statistics
ment changes pact of changes
Design of experiments
Hypothesis testing
Regression analysis
Sampling
Simulation
© ISO 2021 – All rights reserved 5
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SIST ISO 10017:2021
ISO 10017:2021(E)
Table 1 (continued)
Clause/subclause of Quantitative data involved Statistical technique(s)
ISO 9001:2015
8.4 Control of externally provided pro
...
SLOVENSKI STANDARD
oSIST ISO/DIS 10017:2020
01-september-2020
Vodenje kakovosti - Napotki za statistične metode v zvezi z ISO 9001:2015
Quality management - Guidance on statistical techniques for ISO 9001:2015
Lignes directrices pour les techniques statistiques relatives à l'ISO 9001:2015
Ta slovenski standard je istoveten z: ISO/DTR 10017
ICS:
03.120.10 Vodenje in zagotavljanje Quality management and
kakovosti quality assurance
03.120.30 Uporaba statističnih metod Application of statistical
methods
oSIST ISO/DIS 10017:2020 en
2003-01.Slovenski inštitut za standardizacijo. Razmnoževanje celote ali delov tega standarda ni dovoljeno.
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oSIST ISO/DIS 10017:2020
---------------------- Page: 2 ----------------------
oSIST ISO/DIS 10017:2020
DRAFT INTERNATIONAL STANDARD
ISO/DIS 10017
ISO/TC 176/SC 3 Secretariat: NEN
Voting begins on: Voting terminates on:
2020-04-10 2020-07-03
Quality management — Guidance on statistical techniques
for ISO 9001:2015
ICS: 03.120.30; 03.120.10
THIS DOCUMENT IS A DRAFT CIRCULATED
FOR COMMENT AND APPROVAL. IT IS
THEREFORE SUBJECT TO CHANGE AND MAY
NOT BE REFERRED TO AS AN INTERNATIONAL
STANDARD UNTIL PUBLISHED AS SUCH.
IN ADDITION TO THEIR EVALUATION AS
BEING ACCEPTABLE FOR INDUSTRIAL,
This document is circulated as received from the committee secretariat.
TECHNOLOGICAL, COMMERCIAL AND
USER PURPOSES, DRAFT INTERNATIONAL
STANDARDS MAY ON OCCASION HAVE TO
BE CONSIDERED IN THE LIGHT OF THEIR
POTENTIAL TO BECOME STANDARDS TO
WHICH REFERENCE MAY BE MADE IN
Reference number
NATIONAL REGULATIONS.
ISO/DIS 10017:2020(E)
RECIPIENTS OF THIS DRAFT ARE INVITED
TO SUBMIT, WITH THEIR COMMENTS,
NOTIFICATION OF ANY RELEVANT PATENT
RIGHTS OF WHICH THEY ARE AWARE AND TO
©
PROVIDE SUPPORTING DOCUMENTATION. ISO 2020
---------------------- Page: 3 ----------------------
oSIST ISO/DIS 10017:2020
ISO/DIS 10017:2020(E)
COPYRIGHT PROTECTED DOCUMENT
© ISO 2020
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: +41 22 749 01 11
Fax: +41 22 749 09 47
Email: copyright@iso.org
Website: www.iso.org
Published in Switzerland
ii © ISO 2020 – All rights reserved
---------------------- Page: 4 ----------------------
oSIST ISO/DIS 10017:2020
ISO/DIS 10017:2020(E)
Contents Page
Foreword .v
Introduction .vi
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Statistical techniques in the implementation of ISO 9001 . 2
5 Quantitative data and associated statistical techniques in ISO 9001 .2
6 Applicability of selected techniques . 8
7 Description of statistical techniques . 9
7.1 Descriptive statistics . 9
7.1.1 General description . 9
7.1.2 Numerical . 9
7.1.3 Graphical .10
7.1.4 Benefits .10
7.1.5 Limitations and cautions .11
7.1.6 Examples of applications .11
7.2 Design of experiments .11
7.2.1 General description .11
7.2.2 Benefits .12
7.2.3 Limitations and cautions .12
7.2.4 Examples of applications .12
7.3 Hypothesis testing .13
7.3.1 General description .13
7.3.2 Benefits .13
7.3.3 Limitations and cautions .13
7.3.4 Examples of applications .13
7.4 Measurement system analysis .14
7.4.1 General description .14
7.4.2 Benefits .14
7.4.3 Limitations and cautions .14
7.4.4 Examples of applications .15
7.5 Process capability analysis .15
7.5.1 General description .15
7.5.2 Benefits .15
7.5.3 Limitations and cautions .16
7.5.4 Examples of applications .16
7.6 Regression analysis .16
7.6.1 General description .16
7.6.2 Benefits .17
7.6.3 Limitations and cautions .17
7.6.4 Examples of applications .18
7.7 Reliability analysis .18
7.7.1 General description .18
7.7.2 Benefits .19
7.7.3 Limitations and cautions .19
7.7.4 Examples of applications .19
7.8 Sampling .20
7.8.1 General description .20
7.8.2 Benefits .20
7.8.3 Limitations and cautions .20
7.8.4 Examples of applications .21
7.9 Simulation .21
© ISO 2020 – All rights reserved iii
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oSIST ISO/DIS 10017:2020
ISO/DIS 10017:2020(E)
7.9.1 General description .21
7.9.2 Benefits .21
7.9.3 Limitations and cautions .21
7.9.4 Examples of applications .22
7.10 Statistical process control .22
7.10.1 General description .22
7.10.2 Benefits .23
7.10.3 Limitations and cautions .23
7.10.4 Examples of applications .23
7.11 Statistical tolerance .24
7.11.1 General description .24
7.11.2 Benefits .24
7.11.3 Limitations and cautions .24
7.11.4 Examples of applications .25
7.12 Time series analysis .25
7.12.1 General description .25
7.12.2 Benefits .26
7.12.3 Limitations and cautions .26
7.12.4 Examples of applications .26
Bibliography .27
iv © ISO 2020 – All rights reserved
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oSIST ISO/DIS 10017:2020
ISO/DIS 10017:2020(E)
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 176, Quality management and quality
assurance, Subcommittee SC 3, Supporting technologies.
This document cancels and replaces ISO/TR 10017. By decision of ISO/TC 176/SC 3 this work is now
revised as a full guidance standard and aligned with ISO 9001:2015.
This ISO standard may be updated to reflect future revisions of ISO 9001. Comments on the contents of
this standard may be sent to ISO Central Secretariat for consideration in a future revision. 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.
© ISO 2020 – All rights reserved v
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oSIST ISO/DIS 10017:2020
ISO/DIS 10017:2020(E)
Introduction
Statistical techniques can be employed to benefit a wide spectrum of activities and sectors.
The value of statistical techniques follows from the variability that is inherent in the behaviour and
outcome of practically all processes and activities, even under conditions of apparent stability. Such
variability can be observed - over the total life cycle - in the quantifiable characteristics of processes
and the resulting products and services.
Statistical techniques can help to measure, describe, analyse, interpret and model variability (whether
dealing with a relatively limited amount of data or with large data sets). Statistical analysis of data can
provide a better understanding of the nature, extent and causes of variability. It can help to solve and
even prevent problems and mitigate risks that could stem from such variability.
The analysis of available data using statistical techniques can assist in decision making and thereby
help to improve the performance of processes and the resulting products and/or services, to provide
benefits in productivity and cost.
The criteria for determining the need for statistical techniques, and the appropriateness of the
technique(s) selected, remain the prerogative of the organization.
The purpose of this ISO standard is to assist an organization to identify statistical techniques against
the elements of a quality management system as defined by ISO 9001:2015, which may help to improve
processes and the resulting products and services.
This document may be also used to support other management systems and supporting standards
such as, for example, environmental management system, health/safety management system or other
management systems.
vi © ISO 2020 – All rights reserved
---------------------- Page: 8 ----------------------
oSIST ISO/DIS 10017:2020
DRAFT INTERNATIONAL STANDARD ISO/DIS 10017:2020(E)
Quality management — Guidance on statistical techniques
for ISO 9001:2015
1 Scope
This document provides guidance on the selection of appropriate statistical techniques that may be
useful to an organization, irrespective of size or complexity, in developing, implementing, maintaining
and improving a quality management system in compliance with ISO 9001:2015.
Note 1 This standard is not intended for contractual, regulatory or certification/registration purposes. It is
not intended to be used as a mandatory checklist for compliance with ISO 9001:2015 requirements.
Note 2 This standard does not provide guidance on how to use the statistical techniques.
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 3534-1, Statistics — Vocabulary and symbols — Part 1: Probability and general statistical terms
ISO 3534-2, Statistics — Vocabulary and symbols — Part 2: Statistical quality control
ISO 3534-3, Statistics — Vocabulary and symbols — Part 3: Design of experiments
ISO 3534-4, Statistics — Vocabulary and symbols — Part 4: Survey sampling
ISO 9000:2015, Quality management systems — Fundamentals and vocabulary
ISO 9001:2015, Quality management systems — Requirements
3 Terms and definitions
For the purposes of this document, the terms and definitions given in ISO 3534, Parts 1, 2 ,3 and 4 and
in ISO 9000:2015, and the following apply.
ISO and IEC maintain terminological databases for use in standardization at the following addresses:
— ISO Online browsing platform: available at https:// www .iso .org/ obp
— IEC Electropedia: available at http:// www .electropedia .org/
3.1
statistical technique
methodology for the analysis of quantitative data (ISO 9000:2015, 3.8.1) associated with variation in
products, processes, services and phenomena under study to provide information (ISO 9000:2015,
3.8.2) on the object of the study.
Note 1 to entry: Statistical techniques are equally applicable to qualitative (non-numeric) data if such data can be
converted to quantitative (numeric) data
Note 2 to entry: For the purposes of this document, the term “statistical techniques” are interchangeable with
“statistical methods”
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4 Statistical techniques in the implementation of ISO 9001
The justification for using statistical techniques is that their application could help to improve the
effectiveness of the quality management system.
Statistical techniques, or families of techniques, that find useful and ready application in the
implementation of ISO 9001 are listed below (in alphabetical order)
— descriptive statistics;
— design of experiments;
— hypothesis testing;
— measurement system analysis;
— process capability analysis;
— regression analysis;
— reliability analysis;
— sampling;
— simulation;
— statistical process control;
— statistical tolerance;
— time series analysis.
Many of these techniques are used in conjunction with other techniques or as sub-sets of other
statistical techniques.
The list of statistical techniques cited in this standard is neither complete nor exhaustive and does not
preclude the use of any other techniques (statistical or otherwise) that are deemed to be beneficial to the
organization. Furthermore, this standard does not attempt to prescribe which statistical technique(s)
are to be used; nor does it attempt to advise on how the technique(s) are to be implemented.
5 Quantitative data and associated statistical techniques in ISO 9001
Quantitative data that may be reasonably encountered in activities associated with the clauses and
sub-clauses of ISO 9001:2015 is noted in Table 1. Listed against the quantitative data identified are
statistical techniques that could be of potential benefit to the organization when applied to such data.
Where no need for quantitative data could be readily associated with a clause or sub-clause of ISO 9001,
no statistical technique is identified.
The statistical techniques cited in this guidance standard are limited to those that are well known. A
brief description of each of these statistical techniques is given in Clause 7.
The organization can assess the relevance and value of each statistical technique listed in Table 1 and
determine whether it may be useful in the context of that clause.
Table 1 — Quantitative data and possible statistical technique(s)
Clause/sub-clause of Quantitative data involved Statistical technique(s)
ISO 9001:2015
1 Scope Not applicable
2 Normative references Not applicable
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Table 1 (continued)
Clause/sub-clause of Quantitative data involved Statistical technique(s)
ISO 9001:2015
3 Terms and definitions Not applicable
4. Context of the organiza- —
tion
4.1 Understanding the or- Data regarding internal and external Descriptive statistics
ganization and its context issues, for example:
Statistical process control
• Financial
Sampling
• Market research
Time series analysis
• Sales
• Product and service performance
• Competition / benchmarking
4.2 Understanding the Subjective and objective data regarding Descriptive statistics
needs and expectations of expectations of interested parties (e.g.
Sampling
Interested parties market research)
Time series analysis
4.3 Determining the None identified
scope of the quality man-
agement system
4.4 Quality management —
system and its processes
4.4.1 None identified
4.4.2 None identified
5. Leadership —
5.1 Leadership and com- —
mitment
5.1.1 General None Identified
5.1.2 Customer focus None identified
5.2 Policy —
5.2.1 Establishing the qual- None identified
ity policy
5.2.2 Communicating the Data to determine extent to which poli- Descriptive statistics
quality policy cy is understood
Sampling
5.3 Organizational roles, None identified
responsibilities and au-
thorities
6 Planning —
6.1 Actions to address —
risks and opportunities
6.1.1 Business data to assess risks Descriptive statistics
6.1.2 Business data to assess effectiveness Descriptive statistics
of actions
6.2 Quality objectives and —
planning to achieve them
6.2.1 None identified
6.2.2 None identified
6.3 Planning of changes None identified
7 Support —
7.1 Resources —
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Table 1 (continued)
Clause/sub-clause of Quantitative data involved Statistical technique(s)
ISO 9001:2015
7.1.1 General Summary data on capability Descriptive statistics
7.1.2 People None identified
7.1.3 Infrastructure Quantitative data related to the per- Descriptive statistics
formance and reliability of equipment
Process capability analysis
(hardware and software) and trans-
portation Reliability analysis
7.1.4 Environment for the Data on the environment, for example: Descriptive statistics
operation of processes
• Contamination levels Measurement system analysis
• Antistatic controls Process capability analysis
• Temperatures (e.g. bacteria con- Sampling
trol)
Statistical process control
• Morale (e.g. absenteeism)
Time series analysis
7.1.5 Monitoring and meas- —
uring resources
7.1.5.1 General Data relating to measurement capability Descriptive statistics
Measurement system analysis
Statistical tolerance
7.1.5.2 Measurement Data relating to stability of measure- Descriptive statistics
traceability ment systems
Time series analysis
7.1.6 Organizational None identified
knowledge
7.2 Competence Quantitative data on training and ef- Descriptive statistics
fectiveness of training
7.3 Awareness None identified
7.4 Communication None identified
7.5 Documented Informa- —
tion
7.5.1 General None identified
7.5.2 Creating and updating None identified
7.5.3 Control of document- —
ed information
7.5.3.1 None identified
7.5.3.2 None identified
8 Operation —
8.1 Operational planning No specific data identified
and control
8.2 Requirements for prod- —
ucts and services
8.2.1 Customer communi- None identified
cations
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Table 1 (continued)
Clause/sub-clause of Quantitative data involved Statistical technique(s)
ISO 9001:2015
8.2.2 Determining the Data to demonstrate capability and Descriptive statistics
requirements for products organizational performance
Hypothesis testing
and services
Measurement system analysis
Process capability analysis
Regression analysis
Reliability analysis
Sampling
Statis
...
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