Chair: Anna Borowska
Room: S2 Wawel
Time: 09:00 - 10:30
Date: 28 June
|Title: <<< Capabilities – Improving the quality of statistical capacity development >>>
Statistical capacity development is a growing priority for many national and international statistical organisations. They are faced with the challenges of increasing demands to produce new types of statistics, to use new data sources, and to master new technologies. The growing data requirements for monitoring progress towards the sustainable development goals, as well as to provide evidence to address socio-economic challenges such as globalisation and migration, all add to the pressure to increase efficiency. Increasing the quality and effectiveness of statistical capacity development activities is essential if statistical organisations are to meet these challenges. There is a growing recognition that capacity development should be about much more than just providing training courses for staff. A more holistic approach is needed, focusing on improving the capacity of the organisation as well as the capacity of the people who work for it. This paper explores how new tools and concepts, adapted from those used outside the official statistics community, can help. It focuses particularly on the concepts of “capabilities” and “maturity models”, and considers how these concepts can be used to identify priorities more efficiently, and to monitor the effectiveness of capacity development activities.
|Title: <<< A matrix model for human resource organization to improve effectivness and efficiency in official statistics - ISTAT >>>
Quality does not only mean quality of products, services, processes and methodologies, but quality is, first of all, an approach that invests all the organization. In 2016, the Italian national Institute of Statistics (Istat) launched the Modernisation Programme, whose main objective is to enrich the supply and quality of the information produced, while improving the effectiveness and efficiency of overall activity. For what concerns organisational items, Modernisation Programme based on two main focuses regarding centralization of corporate support services,introduction of a portfolio and project management increasing the attention on statistical outputs and the efficient management of resources. In this frameworks, Istat switches from a functional organization to a matrix model of organization that aims to achieve a better human resource management, crucial in a diminishing resources perspective. In Istat matix model, staff knowledge and skills can be shared between functional departments and project teams according to needs. In this organizational model, people who work on projects have basically two leaders: the authority of the functional manager runs vertically downwards and the authority of the project manager runs horizontally. Precisely this crossing between the reporting lines determines the meaning of the matrix. Istat has been experimenting a matrix organizational structure for almost 2 years and we have now elements for an initial assessment of the model. The paper describes how this model has been introduced at Istat, the advantages – both real and potential – of this structure in a statistical environment and the problems to cope with for a full implementation.
|Title: <<< Sensibilization on quality at the training center of Insee >>>
In the training center of Insee (Cefil), the culture of quality is disseminated to the futur staff of the NSI through a process of acculturation. Quality is omnipresent in all the courses and is presented to the trainees in various dimensions going from methodological to ethical dimension.
Different principles of quality are approached through study projects. For example, the project of concerted analysis of statistical tables demonstrates the necessity for the statistician to present the results of his works in a clear and understandable way. By organizing a forum, the skill transmission project emphasizes the importance of pedagogy. The statistical survey project places the trainees in situation to build a collection of data from scratch in order to answer to the request of a public actor. This exercise requires to use every skills of a collective, to meet the deadlines, to restore results in compliance with the statistical secret and to document the data. It teaches the trainees how to manage the impact of a data processing on the final result. The Cefil also offers a classic sequence on quality to the trainees but the education of the training center wouldn’t be efficient enough to the objective of professionalization if it dispensed only this sequence. Indeed, the support of quality is observed to be more induced by a daily behaviour than by a knowledge of an academic subject. Operating in project mode takes there all its interest. The approach of quality is thereby embedded in a holistic conception of the educational route of whom it is a component.
|Title: <<< Matching pairs, agile and pin the tail on the donkey – making quality management relevant to non-statistical staff >>>
Embedding a culture of quality is a key goal for those working towards the 2021 Census, but many non-statistical staff struggle to understand how quality relates to their roles. We gathered feedback from colleagues representing a range of professions to understand these issues and redesigned an introductory quality management course to tailored to the specific needs of the Programme. The course focuses on three key learning objectives; what quality is, why it is important and how we will achieve good quality outcomes, with the aim of broadening its relevance to, and better engaging staff to achieve a quality culture. We started with our corporate quality management strategy and framework, extending this to include additional components for those working in programme management, procurement and technological areas. We then considered how to increase engagement with our course content. Using best practice from other successful trainers, we adopted a more informal approach while maximising impact through collating real-world examples from across the 2011 Census operational experience and a range of professions. We also highlighted the relevance of quality in day-to-day activities through linking the components of our quality framework to existing Agile working practices, demonstrating that staff were already ‘doing’ quality management whether they realised or not. We introduced simple group activities to raise awareness of the dimensions of statistical quality, our programme quality objectives and activities relevant to attendee’s own roles. Linking these examples to the components of our framework and the course objectives and the use of online quizzes reinforced the key learning points. The course has received outstanding feedback for its interactive and inclusive approach which has enabled staff to better engage with its content and understand the relevance to their own roles. This has translated to increased understanding of quality and a higher profile across the programme.
|Title: <<< The new quality strategy in the modernised Italian National Statistical Institute >>>
Under the pressure of common drivers for innovation, the National Statistical Institutes of several countries, including the Italian institute (Istat), have implemented modernisation programmes in their organisations. They are broadly aimed at improving the amount and quality of the statistical information produced, while increasing the efficiency and cost-effectiveness of the organisation. Quality management has a prominent role in the modernisation programmes being an overarching process supporting the organisation at institutional, process and product level. Starting from the early ‘90s, the long-standing Istat quality management investment has produced an advanced and consolidated quality strategy, harmonised with Eurostat guidance, whose main pillars rely on: the setting of shared standards; a spread network of quality pilots; an articulated assessment approach aimed at continuous quality improvement. The initiatives developed so far at Istat, although generally valid, need to be further improved and tailored with respect to the changed statistical production environment and to the shift from an organisation based on domain specific-silos to a more integrated production model. In addition, the tools already developed for documenting, measuring and assessing quality of statistics based on surveys and/or administrative data need to: I) be generalised to cover the unstructured data sources; II) be managed in a different organisational setting and III) be extended to consider process performance. The paper will present a proposal on how to re-organise the quality activities to better support the needs of a modernised statistical organisation. Firstly, each element of the quality strategy will be analysed in the light of the modernised Institute and of the recent orientation provided by the European Statistical System Common Quality Framework. Then, a redesigned approach to process and product quality assessment and improvement will be proposed. Finally, the recent activities focused on the quality improvement of the National Statistical System will be shortly described.
|Title: <<< Future – Engage – Deliver: refreshing the UK Code of Practice for Statistics >>>
We live in a data-rich world that is rapidly changing. This environment impacts us all, as well as the very statistics used to make essential judgements and decisions in all parts of society. In the UK the Code of Practice for Official Statistics has been at the heart of setting high standards since 2009. The changing data landscape and recommendations from Sir Charles Bean’s Independent Review of UK Economic Statistics provided a strong impetus for considering how to ensure the Code continues to remain relevant in driving further improvements in official statistics. We followed a Future – Engage – Deliver model. We envisioned the Future in our Code stock take, conducted from late 2015 to December 2016. Our testing and development of the refreshed Code in the period January to June 2017, in which we conducted a series of focus groups, as well as a formal consultation between July and October 2017, represented the Engage phase. And our Code Consultation informed our Deliver phase, in which we have revised the Code content to reflect stakeholder feedback. The three pillars of Trustworthiness, Quality and Value now form the central framework for the statistical practices.We are focusing on embedding the Code through the development of interactivity and guidance through our website. And we are advocating the application of the Code beyond official statistics, to have a wider reach. Our ambition is for organisations publishing statistics outside of the official statistics community to also apply the Code principles. The fundamental components which form the basis of the Code can acts as guidelines for all publishers of statistical information for the wider benefit of society.