Chair: Jean-Pierre Poncelet
Room: S3B Sukiennice
Time: 09:00 - 10:30
Date: 28 June
Session 3 - papers & presentations
|Title: <<< The Swiss Federal Statistical Office quality, process and risk management system >>>
The proposed abstract by Switzerland focuses on the new quality, process and risk management system of the Swiss Federal Statistical Office (SFSO) introduced in 2016 as well as lessons learned and next steps in this context. Quality, process and risk management are crucial activities for any organization, especially for statistical offices that have to face many challenges in terms of resources and budget, user needs and technological development. Aware of this reality, the SFSO undertook a major revision of its quality management system between 2014 and 2016. During this work, it was also decided to integrate process and risk management in the same system because they are considered as complementary approaches. The main goal of the system is to support and stimulate continuous improvement of SFSO activities and products and ensure compliance with national or international requirements. This system is now operational and lived through a simple and pragmatic mechanism allowing a better coordination of activities in these three areas as well as a better communication of these topics within the hierarchical line. International standards and tools such as the European Statistics Code of Practice (CoP), the Eurostat Quality Assurance Framework (QAF) or the Generic Statistical Business Process Model (GSBPM) have played a central role in the creation of this new system. This system is itself subject to a constant need for continuous improvement. The use of the Generic Activities Model for Statistical Offices (GAMSO) model and other good practices are all development measures that the SFSO intends to take into account for the future.
|Title: <<< GSBPM and ISO as Quality management system tools: Azerbaijan experience >>>
Quality statistical production depends on standardization and quality management of the current statistical system processes. Recent years the application of ISO 9001 international standard along with GSBPM for improvement of activity among statistical institutions incurs certain conflicts and discordance. Several statistical institutions put forward application of ISO and some of them the GSBPM, and cannot identify the more consistent one. State Statistical Committee of the Republic of Azerbaijan follows in its activity the application of GSBPM for systematic management of statistical processes towards delivery quality statistical product to users, and ISO 9001 standard for identification and observance of requirements of quality management system towards obtaining of the quality product. Due to application of GSBPM the creating flexible tool for identification and explanation of processes required for production of official statistics, standardization of management of current statistical processes, and the process mapping was achieved, whereas through the application of ISO 9001 standard the observance of current guidelines and manuals, the application of PDCA cycle in improvement of outputs was gained, as well as appropriate actions were taken to prevent potential inconsistencies by risk-based thinking. Furthermore significant achievements were gained in the field of implementation of monitoring and improvement measures through conduction of internal audits for completion of GSBPM assessment stage. In our opinion, GSBPM and ISO 9001 standard should not be coincided, on the contrary, they have to be applied in parallel and thus improving quality of official statistics and increasing users’ trust should be gained. It is more logical to implement quality and metadata management on the stages and sub-processes of statistical processes through the application of GSBPM. Due to application of ISO 9001 standard the management by the administration becomes easier, furthermore it enables to monitor at what extent the current requirements are followed based on “process approach”.
|Peter Struijs |
|Title: <<< Quality management of methodology for official statistics >>>
Methodology is a cornerstone of official statistics and one of the major factors that contribute to their quality. This is reflected in the Code of Practice for European Statistics, which mentions that "Sound methodology underpins quality statistics". However, methodology is hard to explain to the average user, and so we must find other ways to ensure trust in statistical methodology and to convince users of the quality of official statistical methodology, such as independence of the methodological unit, transparency of methods, peer reviews, methodological reviews, and internal quality management within the methodological unit. In this paper we elaborate these various ways. We show how quality management of a methodological unit may be based on the Code of Practice. We show how the various elements work together, and how the whole of these elements may lead to certification of the methodological unit, for example by EFQM or ISO. In 2017 the department for methodology and process development at Statistics Netherlands has been certified according to ISO-9001. As an example, we discuss the various steps that have been taken to achieve this certification. In particular we focus on the quality procedures for internal and external reports, recommendations and briefs; the quality assurance of statistical development projects in which methodologists and business analysts participate; the quality assurance of methodological course taught to statisticians,
the internal management of the department.
|Title: <<< Innovation and quality culture in INSTAT >>>
INSTAT in the recent years have worked on different activities to fulfil the requirements of the European Code of Practice. Quality is part of these requirements, so National Statistics Office must define their quality policy and make available to the public. INSTAT declares that the following principles: impartiality, quality of processes and products, user orientation, employee orientation, effectiveness of statistical processes, reducing the workload for respondents are taken into account when performing its tasks. To maintain the public confidence in official statistics INSTAT have selected Total Quality Management (TQM) as the general model for quality management, quality assessment and quality improvement. The main objective of this model is to establish a general framework which will ensure that statistical production processes meets the highest standards as regards quality and efficiency. This paper/presentation will provide more detailed information on the quality documentation and provide additional information around the quality reporting for INSTAT products. We will also present how quality culture has progressed since the launch of the first Staff Satisfaction Survey.
|Title: <<< Integrating process documentation and quality management >>>
With the aim of increasing efficiency and productivity, and, above all, improving the quality of its statistical output, the National Statistics Office (NSO) of Malta embarked on a three-year project for the development and expansion of a quality management framework that covers technical issues and ensures business continuity. The main goal of this project is to integrate data and metadata standards and use them as a template for process documentation. This will in turn provide a framework for process quality assessment and improvement. The first phase involved a stock taking exercise to understand better existing processes across all domains, covering technical and operational aspects. The Generic Statistical Business Process Model (GSBPM) was identified as the best model to describe and define the entire cycle of statistical business processes. Additionally, this model provided a basis to agree on standard terminology and to enable further discussions on developing statistical metadata systems and processes, as well a quality and risk management framework. Such institutional tools were virtually non-existent at NSO. Following a series of consultations, training activities and workshops, a number of key domains were identified and duly documented in line with the GSBPM. The proceedings, together with a meticulous consultation and literature review process, allowed the formation of the Quality Management Framework (QMF). Primarily, we define our QMF as a set of technical guidelines focusing on the design, collection, processing and dissemination of statistical processes. Our main objective is to strengthen compliance with the Statistical Code of Practice on a number of quality-related principles. The process leading to the setting up of the QMF also allowed the creation of a series of specific metadata products for our users. We shall ensure a regular review of both process documentation and QMF, to guarantee the application of modern methodologies and harmonisation across domains.