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BS ISO 16355-3:2019

BS ISO 16355-3:2019

$198.66

Applications of statistical and related methods to new technology and product development process – Quantitative approaches for the acquisition of voice of customer and voice of stakeholder

Published By Publication Date Number of Pages
BSI 2019 56
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This document describes quantitative approaches for acquisition of the voice of customer (VOC) and voice of stakeholder (VOS) and its purpose, and provides recommendations on the use of the applicable tools and methods. It is not a management system standard.

NOTE It does not provide requirements or guidelines for organizations to develop and systematically manage their policies, processes, and procedures in order to achieve specific objectives.

Users of this document include all organization functions necessary to assure customer satisfaction, including business planning, marketing, sales, research and development (R&D), engineering, information technology (IT), manufacturing, procurement, quality, production, service, packaging and logistics, support, testing, regulatory, and other phases in hardware, software, service, and system organizations.

PDF Catalog

PDF Pages PDF Title
2 National foreword
8 Foreword
9 Introduction
11 1 Scope
2 Normative references
3 Terms and definitions
12 4 Basic concepts of QFD
5 Integration of quantitative voice of customer (VOC) and voice of stakeholder (VOS) acquisition with customer research methods
6 Types of QFD projects
7 QFD team membership
7.1 QFD uses cross-functional teams
7.2 Core team membership
7.3 Subject matter experts
7.4 QFD team leadership
8 Types of information
8.1 General
8.2 Market strategy and trends
8.2.1 General
13 8.2.2 Analytic network process (ANP)
8.2.3 Porter 5 force competitive analysis
8.2.4 Market position analysis
8.2.5 Project selection
8.3 Market segments
8.3.1 General
8.3.2 Demographic market segmentation
8.3.3 Attitudinal and cultural dimensions
8.3.4 New Kano model studies
8.3.5 Repertory grid technique
8.4 Competitive space
8.4.1 General
14 8.4.2 Benchmarking
8.4.3 Market position analysis
8.4.4 Multidimensional scaling (MDS)
8.4.5 Repertory grid technique
8.5 Customer and stakeholder applications
8.5.1 Frequency of use or application
8.5.2 Robust parameter design
8.6 Customer needs
8.6.1 Functional needs using text analytics and text mining
8.6.2 Emotional or attractive needs using kansei engineering
15 8.7 Prioritization
8.7.1 General
8.7.2 Analytic hierarchy process (AHP)
8.7.3 L-matrices
8.7.4 Cluster analysis
8.7.5 Analytic network process (ANP)
8.7.6 Benchmarking
8.8 Product requirements, feature sets, concept options
8.8.1 Conjoint analysis
8.8.2 Customer needs — Functional requirements matrix (house of quality)
8.8.3 Quantification method III
8.8.4 Regression analysis
8.8.5 Repertory grid technique
16 8.8.6 Text analytics and text mining
8.9 Distribution, logistics and inventory, sales channels
8.10 Customer satisfaction surveys and preference benchmarking
8.10.1 Customer satisfaction surveys
8.10.2 Factor analysis and covariance structure analysis
8.10.3 Fuzzy set theory
8.10.4 Net promoter score (NPS)
8.10.5 Neural networks and artificial intelligence
8.10.6 Regression analysis
17 9 Tools for quantitative VOC and VOS acquisition and analysis
9.1 Analytic network process (ANP)
9.1.1 General
18 9.1.2 Building and analyzing the network
19 9.2 Artificial intelligence (AI)
20 9.3 Conjoint analysis
9.3.1 General
9.3.2 Types of conjoint analyses used with QFD
9.3.3 Building the conjoint analysis survey
21 9.3.4 Case study of conjoint analysis and QFD
22 9.4 Cluster analysis
9.5 Cultural dimensions
9.5.1 General
23 9.5.2 Cultural dimension scores
9.5.3 Cultural dimensions and QFD
9.6 Factor analysis with covariance structure analysis
9.6.1 General
9.6.2 Factor analysis to classify functional requirements into satisfaction factors
24 9.6.3 Covariance structure analysis
9.7 Fuzzy set theory and multi-attribute utility theory
9.7.1 General
9.7.2 Difficulties in scoring customer satisfaction
9.7.3 Fuzzy sets
25 9.7.4 Crisp scores
9.7.5 Customer preferences by benchmarking competition
9.7.6 Failure mode and effects analysis using fuzzy multiple-objective decision models
26 9.8 Market position analysis
9.8.1 General
9.8.2 Types of market positioning
9.9 Market segmentation using cross tabulations
9.9.1 General
27 9.9.2 Types of cross tabulations
28 9.9.3 Uses of cross tabulations
9.10 Multidimensional scaling (MDS)
9.10.1 General
9.10.2 Conducting the MDS study
29 9.10.3 Case study on toothpaste
30 9.11 Net promoter score (NPS)
9.11.1 General
9.11.2 NPS survey
9.11.3 NPS survey results
31 9.12 Neural networks (NN)
9.12.1 General
9.12.2 Preparing the surveys
32 9.12.3 Interpreting the NN output
9.12.4 Using the NN output in a QFD study
9.13 Quantification methods (QM)
9.13.1 General
33 9.13.2 Quantification method III (QM III)
9.13.3 Applying QM III to a 2-dimensional QFD matrix
37 9.14 Regression analysis
9.14.1 General
38 9.14.2 Regression analysis in QFD
9.14.3 Regression data
40 9.15 Repertory grid technique
9.15.1 General
9.15.2 The repertory grid technique process
41 9.16 Text analytics and text mining
9.16.1 General
9.16.2 Text clustering
42 9.16.3 Topic modelling
43 10 Deployment to next stage
10.1 Customer needs related information
10.2 Product related information
44 Annex A (informative) Using sampling surveys
52 Bibliography

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BS ISO 16355-3:2019
$198.66